| 1. |
- Lam, Thua-Phong, et al.
(författare)
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Flavonoids as dual-target inhibitors against α-glucosidase and α-amylase : a systematic review of in vitro studies
- 2024
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Ingår i: NATURAL PRODUCTS AND BIOPROSPECTING. - : Springer. - 2192-2195 .- 2192-2209. ; 14:1
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Forskningsöversikt (refereegranskat)abstract
- Diabetes mellitus remains a major global health issue, and great attention is directed at natural therapeutics. This systematic review aimed to assess the potential of flavonoids as antidiabetic agents by investigating their inhibitory effects on alpha-glucosidase and alpha-amylase, two key enzymes involved in starch digestion. Six scientific databases (PubMed, Virtual Health Library, EMBASE, SCOPUS, Web of Science, and WHO Global Index Medicus) were searched until August 21, 2022, for in vitro studies reporting IC50 values of purified flavonoids on alpha-amylase and alpha-glucosidase, along with corresponding data for acarbose as a positive control. A total of 339 eligible articles were analyzed, resulting in the retrieval of 1643 flavonoid structures. These structures were rigorously standardized and curated, yielding 974 unique compounds, among which 177 flavonoids exhibited inhibition of both alpha-glucosidase and alpha-amylase are presented. Quality assessment utilizing a modified CONSORT checklist and structure-activity relationship (SAR) analysis were performed, revealing crucial features for the simultaneous inhibition of flavonoids against both enzymes. Moreover, the review also addressed several limitations in the current research landscape and proposed potential solutions. The curated datasets are available online at https://github.com/MedChemUMP/FDIGA.
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| 2. |
- Pham, Binh Thai, et al.
(författare)
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Performance Evaluation of Machine Learning Methods for Forest Fire Modeling and Prediction
- 2020
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Ingår i: Symmetry. - Switzerland : MDPI. - 2073-8994. ; 12:6
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Tidskriftsartikel (refereegranskat)abstract
- Predicting and mapping fire susceptibility is a top research priority in fire-prone forests worldwide. This study evaluates the abilities of the Bayes Network (BN), Naïve Bayes (NB), Decision Tree (DT), and Multivariate Logistic Regression (MLP) machine learning methods for the prediction and mapping fire susceptibility across the Pu Mat National Park, Nghe An Province, Vietnam. The modeling methodology was formulated based on processing the information from the 57 historical fires and a set of nine spatially explicit explanatory variables, namely elevation, slope degree, aspect, average annual temperate, drought index, river density, land cover, and distance from roads and residential areas. Using the area under the receiver operating characteristic curve (AUC) and seven other performance metrics, the models were validated in terms of their abilities to elucidate the general fire behaviors in the Pu Mat National Park and to predict future fires. Despite a few differences between the AUC values, the BN model with an AUC value of 0.96 was dominant over the other models in predicting future fires. The second best was the DT model (AUC = 0.94), followed by the NB (AUC = 0.939), and MLR (AUC = 0.937) models. Our robust analysis demonstrated that these models are sufficiently robust in response to the training and validation datasets change. Further, the results revealed that moderate to high levels of fire susceptibilities are associated with ~19% of the Pu Mat National Park where human activities are numerous. This study and the resultant susceptibility maps provide a basis for developing more efficient fire-fighting strategies and reorganizing policies in favor of sustainable management of forest resources.
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| 3. |
- Ha, Duong Hai, et al.
(författare)
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Quadratic Discriminant Analysis Based Ensemble Machine Learning Models for Groundwater Potential Modeling and Mapping
- 2021
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Ingår i: Water resources management. - : Springer. - 0920-4741 .- 1573-1650. ; 35:13, s. 4415-4433
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Tidskriftsartikel (refereegranskat)abstract
- In this study, the AdaBoost, MultiBoost and RealAdaBoost methods were combined with the Quadratic Discriminant Analysis method to develop three new GIS-based Machine Learning ensemble models, i.e., ABQDA, MBQDA, and RABQDA for groundwater potential mapping in the Dak Nong Province, Vietnam. In total, 227 groundwater wells and 12 conditioning factors (infiltration, rainfall, river density, topographic wetness index, sediment transport index, stream power index, elevation, aspect, curvature, slope, soil, and land use) were used for this study. Performance of the models was evaluated using the Area Under the Receiver Operating Characteristics Curve AUC (AUC) and several other performance metrics. The results showed that the ABQDA model that achieved AUC = 0.741 was superior to the other models in producing an accurate map of groundwater potential for the Dak Nong Province. The models and potential maps produced here can help policymakers and water resources managers to preserve an optimal exploit from these vital resources.
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| 4. |
- Nguyen, Phong Tung, et al.
(författare)
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Groundwater Potential Mapping Combining Artificial Neural Network and Real AdaBoost Ensemble Technique : The DakNong Province Case-study, Vietnam
- 2020
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Ingår i: International Journal of Environmental Research and Public Health. - Switzerland : MDPI. - 1661-7827 .- 1660-4601. ; 17:7
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Tidskriftsartikel (refereegranskat)abstract
- The main aim of this study is to assess groundwater potential of the DakNong province, Vietnam, using an advanced ensemble machine learning model (RABANN) that integrates Artificial Neural Networks (ANN) with RealAdaBoost (RAB) ensemble technique. For this study, twelve conditioning factors and wells yield data was used to create the training and testing datasets for the development and validation of the ensemble RABANN model. Area Under the Receiver Operating Characteristic (ROC) curve (AUC) and several statistical performance measures were used to validate and compare performance of the ensemble RABANN model with the single ANN model. Results of the model studies showed that both models performed well in the training phase of assessing groundwater potential (AUC ≥ 0.7), whereas the ensemble model (AUC = 0.776) outperformed the single ANN model (AUC = 0.699) in the validation phase. This demonstrated that the RAB ensemble technique was successful in improving the performance of the single ANN model. By making minor adjustment in the input data, the ensemble developed model can be adapted for groundwater potential mapping of other regions and countries toward more efficient water resource management. The present study would be helpful in improving the groundwater condition of the area thus in solving water borne disease related health problem of the population.
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| 5. |
- Nguyen, Phong Tung, et al.
(författare)
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Improvement of Credal Decision Trees Using Ensemble Frameworks for Groundwater Potential Modeling
- 2020
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Ingår i: Sustainability. - Switzerland : MDPI. - 2071-1050. ; 12:7
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Tidskriftsartikel (refereegranskat)abstract
- Groundwater is one of the most important sources of fresh water all over the world, especially in those countries where rainfall is erratic, such as Vietnam. Nowadays, machine learning (ML) models are being used for the assessment of groundwater potential of the region. Credal decision trees (CDT) is one of the ML models which has been used in such studies. In the present study, the performance of the CDT has been improved using various ensemble frameworks such as Bagging, Dagging, Decorate, Multiboost, and Random SubSpace. Based on these methods, five hybrid models, namely BCDT, Dagging-CDT, Decorate-CDT, MBCDT, and RSSCDT, were developed and applied for groundwater potential mapping of DakLak province of Vietnam. Data of 227 groundwater wells of the study area were utilized for the construction and validation of the models. Twelve groundwater potential conditioning factors, namely rainfall, slope, elevation, river density, Sediment Transport Index (STI), curvature, flow direction, aspect, soil, land use, Topographic Wetness Index (TWI), and geology, were considered for the model studies. Various statistical measures, including area under receiver operating characteristic (AUC) curve, were applied to validate and compare the performance of the models. The results show that performance of the hybrid CDT ensemble models MBCDT (AUC = 0.770), BCDT (AUC = 0.731), Dagging-CDT (AUC = 0.763), Decorate-CDT (AUC = 0.750), and RSSCDT (AUC = 0.766) improved significantly in comparison to the single CDT (AUC = 0.722) model. Therefore, these developed hybrid models can be applied for better ground water potential mapping and groundwater resources management of the study area as well as other regions of the world.
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| 6. |
- Nguyen, Phong Tung, et al.
(författare)
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Soft Computing Ensemble Models Based on Logistic Regression for Groundwater Potential Mapping
- 2020
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Ingår i: Applied Sciences. - Switzerland : MDPI. - 2076-3417. ; 10:7
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Tidskriftsartikel (refereegranskat)abstract
- Groundwater potential maps are one of the most important tools for the management of groundwater storage resources. In this study, we proposed four ensemble soft computing models based on logistic regression (LR) combined with the dagging (DLR), bagging (BLR), random subspace (RSSLR), and cascade generalization (CGLR) ensemble techniques for groundwater potential mapping in Dak Lak Province, Vietnam. A suite of well yield data and twelve geo-environmental factors (aspect, elevation, slope, curvature, Sediment Transport Index, Topographic Wetness Index, flow direction, rainfall, river density, soil, land use, and geology) were used for generating the training and validation datasets required for the building and validation of the models. Based on the area under the receiver operating characteristic curve (AUC) and several other validation methods (negative predictive value, positive predictive value, root mean square error, accuracy, sensitivity, specificity, and Kappa), it was revealed that all four ensemble learning techniques were successful in enhancing the validation performance of the base LR model. The ensemble DLR model (AUC = 0.77) was the most successful model in identifying the groundwater potential zones in the study area, followed by the RSSLR (AUC = 0.744), BLR (AUC = 0.735), CGLR (AUC = 0.715), and single LR model (AUC = 0.71), respectively. The models developed in this study and the resulting potential maps can assist decision-makers in the development of effective adaptive groundwater management plans.
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| 7. |
- Nguyen-Tien, Thang, et al.
(författare)
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The Distribution and Composition of Vector Abundance in Hanoi City, Vietnam : Association with Livestock Keeping and Flavivirus Detection
- 2021
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Ingår i: Viruses. - : MDPI. - 1999-4915. ; 13:11
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Tidskriftsartikel (refereegranskat)abstract
- Background: Dengue virus and Japanese encephalitis virus are two common flaviviruses that are spread widely by Aedes and Culex mosquitoes. Livestock keeping is vital for cities; however, it can pose the risk of increasing the mosquito population. Our study explored how livestock keeping in and around a large city is associated with the presence of mosquitoes and the risk of them spreading flaviviruses.Methods: An entomological study was conducted in 6 districts with 233 households with livestock, and 280 households without livestock, in Hanoi city. BG-Sentinel traps and CDC light traps were used to collect mosquitoes close to animal farms and human habitats. Adult mosquitoes were counted, identified to species level, and grouped into 385 pools, which were screened for flaviviruses using a pan-flavivirus qPCR protocol and sequencing.Results: A total of 12,861 adult mosquitoes were collected at the 513 households, with 5 different genera collected, of which the Culex genus was the most abundant. Our study found that there was a positive association between livestock keeping and the size of the mosquito population-most predominantly between pig rearing and Culex species (p < 0.001). One pool of Cx. tritaeniorhynchus, collected in a peri-urban district, was found to be positive for Japanese encephalitis virus.Conclusions: The risk of flavivirus transmission in urban areas of Hanoi city due to the spread of Culex and Aedes mosquitoes could be facilitated by livestock keeping.
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| 8. |
- Nguyen, Viet-Tien, et al.
(författare)
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GIS Based Novel Hybrid Computational Intelligence Models for Mapping Landslide Susceptibility : A Case Study at Da Lat City, Vietnam
- 2019
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Ingår i: Sustainability. - Switzerland : MDPI. - 2071-1050. ; 11:24
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Tidskriftsartikel (refereegranskat)abstract
- Landslides affect properties and the lives of a large number of people in many hilly parts of Vietnam and in the world. Damages caused by landslides can be reduced by understanding distribution, nature, mechanisms and causes of landslides with the help of model studies for better planning and risk management of the area. Development of landslide susceptibility maps is one of the main steps in landslide management. In this study, the main objective is to develop GIS based hybrid computational intelligence models to generate landslide susceptibility maps of the Da Lat province, which is one of the landslide prone regions of Vietnam. Novel hybrid models of alternating decision trees (ADT) with various ensemble methods, namely bagging, dagging, MultiBoostAB, and RealAdaBoost, were developed namely B-ADT, D-ADT, MBAB-ADT, RAB-ADT, respectively. Data of 72 past landslide events was used in conjunction with 11 landslide conditioning factors (curvature, distance from geological boundaries, elevation, land use, Normalized Difference Vegetation Index (NDVI), relief amplitude, stream density, slope, lithology, weathering crust and soil) in the development and validation of the models. Area under the receiver operating characteristic (ROC) curve (AUC), and several statistical measures were applied to validate these models. Results indicated that performance of all the models was good (AUC value greater than 0.8) but B-ADT model performed the best (AUC= 0.856). Landslide susceptibility maps generated using the proposed models would be helpful to decision makers in the risk management for land use planning and infrastructure development.
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| 9. |
- Pham, Binh Thai, et al.
(författare)
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A Comparative Study of Kernel Logistic Regression, Radial Basis Function Classifier, Multinomial Naïve Bayes, and Logistic Model Tree for Flash Flood Susceptibility Mapping
- 2020
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Ingår i: Water. - Switzerland : MDPI. - 2073-4441. ; 12:1, s. 1-21
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Tidskriftsartikel (refereegranskat)abstract
- Risk of flash floods is currently an important problem in many parts of Vietnam. In this study, we used four machine-learning methods, namely Kernel Logistic Regression (KLR), Radial Basis Function Classifier (RBFC), Multinomial Naïve Bayes (NBM), and Logistic Model Tree (LMT) to generate flash flood susceptibility maps at the minor part of Nghe An province of the Center region (Vietnam) where recurrent flood problems are being experienced. Performance of these four methods was evaluated to select the best method for flash flood susceptibility mapping. In the model studies, ten flash flood conditioning factors, namely soil, slope, curvature, river density, flow direction, distance from rivers, elevation, aspect, land use, and geology, were chosen based on topography and geo-environmental conditions of the site. For the validation of models, the area under Receiver Operating Characteristic (ROC), Area Under Curve (AUC), and various statistical indices were used. The results indicated that performance of all the models is good for generating flash flood susceptibility maps (AUC = 0.983–0.988). However, performance of LMT model is the best among the four methods (LMT: AUC = 0.988; KLR: AUC = 0.985; RBFC: AUC = 0.984; and NBM: AUC = 0.983). The present study would be useful for the construction of accurate flash flood susceptibility maps with the objectives of identifying flood-susceptible areas/zones for proper flash flood risk management.
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| 10. |
- Tran, Trung-Hieu, et al.
(författare)
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GIS-Based Soft Computing Models for Landslide Susceptibility Mapping: A Case Study of Pithoragarh District, Uttarakhand State, India
- 2021
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Ingår i: Mathematical problems in engineering (Print). - : Hindawi Publishing Corporation. - 1024-123X .- 1563-5147. ; 2021
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Tidskriftsartikel (refereegranskat)abstract
- The main objective of the study was to investigate performance of three soft computing models: Naïve Bayes (NB), Multilayer Perceptron (MLP) neural network classifier, and Alternating Decision Tree (ADT) in landslide susceptibility mapping of Pithoragarh District of Uttarakhand State, India. For this purpose, data of 91 past landslide locations and ten landslide influencing factors, namely, slope degree, curvature, aspect, land cover, slope forming materials (SFM), elevation, distance to rivers, geomorphology, overburden depth, and distance to roads were considered in the models study. Thematic maps of the Geological Survey of India (GSI), Google Earth images, and Aster Digital Elevation Model (DEM) were used for the development of landslide susceptibility maps in the Geographic Information System (GIS) environment. Landslide locations data was divided into a 70 : 30 ratio for the training (70%) and testing/validation (30%) of the three models. Standard statistical measures, namely, Positive Predicted Values (PPV), Negative Predicted Values (NPV), Sensitivity, Specificity, Mean Absolute Error (MAE), Root Mean Squire Error (RMSE), and Area under the ROC Curve (AUC) were used for the evaluation of the models. All the three soft computing models used in this study have shown good performance in the accurate development of landslide susceptibility maps, but performance of the ADT and MLP is better than NB. Therefore, these models can be used for the construction of accurate landslide susceptibility maps in other landslide-prone areas also.
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| 11. |
- Dung, Nguyen Van, et al.
(författare)
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Exploring novel hybrid soft computing models for landslide susceptibility mapping in Son La hydropower reservoir basin
- 2021
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Ingår i: Geomatics, Natural Hazards and Risk. - : Taylor & Francis. - 1947-5705 .- 1947-5713. ; 12:1, s. 1688-1714
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Tidskriftsartikel (refereegranskat)abstract
- In this study, two novel hybrid models namely Bagging-based Rough Set (BRS) and AdaBoost-based Rough Set (ABRS) were used to generate landslide susceptibility maps of Son La hydropower reservoir basin, Vietnam. In total, 186 past landslide events and twelve landslides affecting factors (slope degree, slope aspect, elevation, curvature, focal flow, river density, rainfall, aquifer, weathering crust, lithology, fault density and road density) were considered in the modeling study. The landslide data was split into training (70%) and testing (30%) for the model's development and validation. One R feature selection method was used to select and prioritize the landslide affecting factors based on their importance in model prediction. Performance of the hybrid developed models was evaluated and also compared with single rough set (RS) and support vector machine (SVM) models using various standard statistical measures including area under the curve (AUC)-receiver operating characteristics (ROC) curve. The results show that the developed hybrid model BRS (AUC = 0.845) is the most accurate model in comparison to other models (ABRS, SVM and RS) in predicting landslide susceptibility. Therefore, the BRS model can be used as an effective tool in the development of an accurate landslide susceptibility map of the hilly area.
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| 12. |
- Duyen, Nguyen Thi, et al.
(författare)
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Steroid glycosides isolated from Paris polyphylla var. chinensis aerial parts and paris saponin II induces G1/S-phase MCF-7 cell cycle arrest
- 2022
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Ingår i: Carbohydrate Research. - : Elsevier BV. - 0008-6215. ; 519
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Tidskriftsartikel (refereegranskat)abstract
- In our previous research on Vietnamese medicinal plants, we found that the ethanolic extract of the aerial parts of Paris polyphylla var. chinensis exhibited cytotoxic effects in vitro in the MCF-7 human cancer cell line. Here, we used combined chromatographic separations to isolate six compounds including a new steroid glycoside, paripoloside A (3), and five known compounds, from the butanol extract of the aerial parts of P. polyphylla. We unambiguously elucidated their structures based on spectroscopic data (proton and carbon-13 nuclear magnetic resonance, heteronuclear single quantum coherence, heteronuclear multiple bond correlation, correlation spectroscopy, and high-resolution electrospray ionization mass spectroscopy data), and chemical reactions. Among the isolated compounds, paris saponin II (PSII) had the strongest cytotoxic effects against MCF-7 breast cancer cells. Interestingly, PSII significantly increased the expression of p53, p21, p27, and Bax protein levels and significantly suppressed the expression of cyclin D1 and retinoblastoma protein. These data suggest that PSII may induce G1/S phase cell cycle arrest and apoptosis pathway development in MCF-7 cells. Furthermore, the MCF-7 breast cancer cells mechanism of PSII was also investigated using molecular docking. Together, our results demonstrate that isolated compounds from P. polyphylla are promising candidates as breast cancer inhibitors.
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| 13. |
- Kochenova, Olga V, et al.
(författare)
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Yeast DNA polymerase ζ maintains consistent activity and mutagenicity across a wide range of physiological dNTP concentrations
- 2017
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Ingår i: Nucleic Acids Research. - : Oxford University Press (OUP). - 0305-1048 .- 1362-4962. ; 45:3, s. 1200-1218
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Tidskriftsartikel (refereegranskat)abstract
- In yeast, dNTP pools expand drastically during DNA damage response. We show that similar dNTP elevation occurs in strains, in which intrinsic replisome defects promote the participation of error-prone DNA polymerase ζ (Polζ) in replication of undamaged DNA. To understand the significance of dNTP pools increase for Polζ function, we studied the activity and fidelity of four-subunit Polζ (Polζ4) and Polζ4-Rev1 (Polζ5) complexes in vitro at 'normal S-phase' and 'damage-response' dNTP concentrations. The presence of Rev1 inhibited the activity of Polζ and greatly increased the rate of all three 'X-dCTP' mispairs, which Polζ4 alone made extremely inefficiently. Both Polζ4 and Polζ5 were most promiscuous at G nucleotides and frequently generated multiple closely spaced sequence changes. Surprisingly, the shift from 'S-phase' to 'damage-response' dNTP levels only minimally affected the activity, fidelity and error specificity of Polζ complexes. Moreover, Polζ-dependent mutagenesis triggered by replisome defects or UV irradiation in vivo was not decreased when dNTP synthesis was suppressed by hydroxyurea, indicating that Polζ function does not require high dNTP levels. The results support a model wherein dNTP elevation is needed to facilitate non-mutagenic tolerance pathways, while Polζ synthesis represents a unique mechanism of rescuing stalled replication when dNTP supply is low.
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| 14. |
- Le, Phu Tran Phong, et al.
(författare)
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Tailoring Vanadium Dioxide Film Orientation Using Nanosheets : a Combined Microscopy, Diffraction, Transport, and Soft X-Ray in Transmission Study
- 2020
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Ingår i: Advanced Functional Materials. - : WILEY-V C H VERLAG GMBH. - 1616-301X .- 1616-3028. ; 30:1
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Tidskriftsartikel (refereegranskat)abstract
- Vanadium dioxide (VO2) is a much-discussed material for oxide electronics and neuromorphic computing applications. Here, heteroepitaxy of VO2 is realized on top of oxide nanosheets that cover either the amorphous silicon dioxide surfaces of Si substrates or X-ray transparent silicon nitride membranes. The out-of-plane orientation of the VO2 thin films is controlled at will between (011)(M1)/(110)(R) and (-402)(M1)/(002)(R) by coating the bulk substrates with Ti0.87O2 and NbWO6 nanosheets, respectively, prior to VO2 growth. Temperature-dependent X-ray diffraction and automated crystal orientation mapping in microprobe transmission electron microscope mode (ACOM-TEM) characterize the high phase purity, the crystallographic and orientational properties of the VO2 films. Transport measurements and soft X-ray absorption in transmission are used to probe the VO2 metal-insulator transition, showing results of a quality equal to those from epitaxial films on bulk single-crystal substrates. Successful local manipulation of two different VO2 orientations on a single substrate is demonstrated using VO2 grown on lithographically patterned lines of Ti0.87O2 and NbWO6 nanosheets investigated by electron backscatter diffraction. Finally, the excellent suitability of these nanosheet-templated VO2 films for advanced lensless imaging of the metal-insulator transition using coherent soft X-rays is discussed.
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| 15. |
- Ngo, Trinh Quoc, et al.
(författare)
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Landslide Susceptibility Mapping Using Single Machine Learning Models : A Case Study from Pithoragarh District, India
- 2021
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Ingår i: Advances in Civil Engineering / Hindawi. - : Hindawi Publishing Corporation. - 1687-8086 .- 1687-8094. ; 2021
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Tidskriftsartikel (refereegranskat)abstract
- Landslides are one of the most devastating natural hazards causing huge loss of life and damage to properties and infrastructures and adversely affecting the socioeconomy of the country. Landslides occur in hilly and mountainous areas all over the world. Single, ensemble, and hybrid machine learning (ML) models have been used in landslide studies for better landslide susceptibility mapping and risk management. In the present study, we have used three single ML models, namely, linear discriminant analysis (LDA), logistic regression (LR), and radial basis function network (RBFN), for landslide susceptibility mapping at Pithoragarh district, as these models are easy to apply and so far they have not been used for landslide study in this area. The main objective of this study is to evaluate the performance of these single models for correctly identifying landslide susceptible zones for their further application in other areas. For this, ten important landslide affecting factors, namely, slope, aspect, curvature, elevation, land cover, lithology, geomorphology, distance to rivers, distance to roads, and overburden depth based on the local geoenvironmental conditions, were considered for the modeling. Landslide inventory of past 398 landslide events was used in the development of models. The data of past landslide events (locations) was randomly divided into a 70/30 ratio for training (70%) and validation (30%) of the models. Standard statistical measures, namely, accuracy (ACC), specificity (SPF), sensitivity (SST), positive predictive value (PPV), negative predictive value (NPV), Kappa, root mean square error (RMSE), and area under the receiver operating characteristic curve (AUC), were used to evaluate the performance of the models. Results indicated that the performance of all the models is very good (AUC > 0.90) and that of the LR model is the best (AUC = 0.926). Therefore, these single ML models can be used for the development of accurate landslide susceptibility maps. Our study demonstrated that the single models which are easy to use and can compete with the complex ensemble/hybrid models can be applied for landslide susceptibility mapping in landslide-prone areas.
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| 16. |
- Pettinari, Matteo, et al.
(författare)
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Impact of the Regulation Strategy on the Transient Behavior of a Brayton Heat Pump
- 2024
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Ingår i: Energies. - : Multidisciplinary Digital Publishing Institute (MDPI). - 1996-1073. ; 17:5
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Tidskriftsartikel (refereegranskat)abstract
- High-temperature heat pumps are a key technology for enabling the complete integration of renewables into the power grid. Although these systems may come with several variants, Brayton heat pumps are gaining more and more interest because of the higher heat sink temperatures and the potential to leverage already existing components in the industry. Because these systems utilize renewable electricity to supply high-temperature heat, they are particularly suited for industry or energy storage applications, thus prompting the development of various demonstration plants to evaluate their performance and flexibility. Adapting to varying load conditions and swiftly responding to load adjustments represent crucial aspects for advancing such systems. In this context, this study delves into assessing the transient capabilities of Brayton heat pumps during thermal load management. A transient model of an emerging prototype is presented, comprising thermal and volume dynamics of the components. Furthermore, two reference scenarios are examined to assess the transient performance of the system, namely a thermal load alteration due to an abrupt change in the desired heat sink temperature and, secondly, to a sudden variation in the sink mass flow rate. Finally, two control methodologies—motor/compressor speed variation and fluid inventory control—are analyzed in the latter scenario, and a comparative analysis of their effectiveness is discussed. Results indicate that varying the compressor speed allows for a response time in the 8–20 min range for heat sink temperature regulation (first scenario). However, the regulation time is conditioned by the maximum thermal stress sustained by the heat exchangers. In the latter scenario, regulating the compressor speed shows a faster response time than the inventory control (2–5 min vs. 15 min). However, the inventory approach provides higher COPs in part-load conditions and better stability during the transient phase.
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| 17. |
- Pham, Binh Thai, et al.
(författare)
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GIS Based Hybrid Computational Approaches for Flash Flood Susceptibility Assessment
- 2020
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Ingår i: Water. - Switzerland : MDPI. - 2073-4441. ; 12:3, s. 1-29
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Tidskriftsartikel (refereegranskat)abstract
- Flash floods are one of the most devastating natural hazards; they occur within a catchment (region) where the response time of the drainage basin is short. Identification of probable flash flood locations and development of accurate flash flood susceptibility maps are important for proper flash flood management of a region. With this objective, we proposed and compared several novel hybrid computational approaches of machine learning methods for flash flood susceptibility mapping, namely AdaBoostM1 based Credal Decision Tree (ABM-CDT); Bagging based Credal Decision Tree (Bag-CDT); Dagging based Credal Decision Tree (Dag-CDT); MultiBoostAB based Credal Decision Tree (MBAB-CDT), and single Credal Decision Tree (CDT). These models were applied at a catchment of Markazi state in Iran. About 320 past flash flood events and nine flash flood influencing factors, namely distance from rivers, aspect, elevation, slope, rainfall, distance from faults, soil, land use, and lithology were considered and analyzed for the development of flash flood susceptibility maps. Correlation based feature selection method was used to validate and select the important factors for modeling of flash floods. Based on this feature selection analysis, only eight factors (distance from rivers, aspect, elevation, slope, rainfall, soil, land use, and lithology) were selected for the modeling, where distance to rivers is the most important factor for modeling of flash flood in this area. Performance of the models was validated and compared by using several robust metrics such as statistical measures and Area Under the Receiver Operating Characteristic (AUC) curve. The results of this study suggested that ABM-CDT (AUC = 0.957) has the best predictive capability in terms of accuracy, followed by Dag-CDT (AUC = 0.947), MBAB-CDT (AUC = 0.933), Bag-CDT (AUC = 0.932), and CDT (0.900), respectively. The proposed methods presented in this study would help in the development of accurate flash flood susceptible maps of watershed areas not only in Iran but also other parts of the world.
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| 18. |
- Pham, Binh Thai, et al.
(författare)
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Improving Voting Feature Intervals for Spatial Prediction of Landslides
- 2020
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Ingår i: Mathematical problems in engineering (Print). - UK : Hindawi Publishing Corporation. - 1024-123X .- 1563-5147. ; 2020
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Tidskriftsartikel (refereegranskat)abstract
- In this study, the main aim is to improve performance of the voting feature intervals (VFIs), which is one of the most effective machine learning models, using two robust ensemble techniques, namely, AdaBoost and MultiBoost for landslide susceptibility assessment and prediction. For this, two hybrid models, namely, AdaBoost-based Voting Feature Intervals (ABVFIs) and MultiBoost-based Voting Feature Intervals (MBVFIs) were developed and validated using landslide data collected from one of the landslide affected districts of Vietnam, namely, Muong Lay. Quantitative validation methods including area under the ROC curve (AUC) were used to evaluate model performance. The results indicated that both the newly developed ensemble models ABVFI (AUC = 0.859) and MBVFI (AUC = 0.839) outperformed the single VFI (AUC = 0.824) model. Thus, ensemble framework-based VFI algorithms can be used for the accurate spatial prediction of landslides, which can also be applied in other landslide prone regions of the world. Landslide susceptibility maps developed by ensemble VFI models can be used for better landslide prevention and risk management of the area.
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| 19. |
- Rentoft, Matilda, et al.
(författare)
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Heterozygous colon cancer-associated mutations of SAMHD1 have functional significance
- 2016
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Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 113:17, s. 4723-4728
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Tidskriftsartikel (refereegranskat)abstract
- Even small variations in dNTP concentrations decrease DNA replication fidelity, and this observation prompted us to analyze genomic cancer data for mutations in enzymes involved in dNTP metabolism. We found that sterile alpha motif and histidine-aspartate domain-containing protein 1 (SAMHD1), a deoxyribonucleoside triphosphate triphosphohydrolase that decreases dNTP pools, is frequently mutated in colon cancers, that these mutations negatively affect SAMHD1 activity, and that severalSAMHD1mutations are found in tumors with defective mismatch repair. We show that minor changes in dNTP pools in combination with inactivated mismatch repair dramatically increase mutation rates. Determination of dNTP pools in mouse embryos revealed that inactivation of oneSAMHD1allele is sufficient to elevate dNTP pools. These observations suggest that heterozygous cancer-associatedSAMHD1mutations increase mutation rates in cancer cells.
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| 20. |
- Repolês, Bruno Marçal, et al.
(författare)
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The integrity and assay performance of tissue mitochondrial DNA is considerably affected by choice of isolation method
- 2021
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Ingår i: Mitochondrion (Amsterdam. Print). - : Elsevier. - 1567-7249 .- 1872-8278. ; 61, s. 179-187
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Tidskriftsartikel (refereegranskat)abstract
- The integrity of mitochondrial DNA (mtDNA) isolated from solid tissues is critical for analyses such as long-range PCR, but is typically assessed under conditions that fail to provide information on the individual mtDNA strands. Using denaturing gel electrophoresis, we show that commonly-used isolation procedures generate mtDNA containing several single-strand breaks per strand. Through systematic comparison of DNA isolation methods, we identify a procedure yielding the highest integrity of mtDNA that we demonstrate displays improved performance in downstream assays. Our results highlight the importance of isolation method choice, and serve as a resource to researchers requiring high-quality mtDNA from solid tissues.
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| 21. |
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| 22. |
- Sharma, Sushma, et al.
(författare)
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Quantitative analysis of nucleoside triphosphate pools in mouse muscle using hydrophilic interaction liquid chromatography coupled with tandem mass spectrometry detection
- 2023
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Ingår i: Mitochondrial DNA. - New York : Humana Press. - 9781071629215 - 9781071629222 ; , s. 267-280
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Bokkapitel (refereegranskat)abstract
- Defects in deoxyribonucleoside triphosphate (dNTP) metabolism are associated with a number of mitochondrial DNA (mtDNA) depletion syndromes (MDS). These disorders affect the muscles, liver, and brain, and the concentrations of dNTPs in these tissues are already normally low and are, therefore, difficult to measure. Thus, information about the concentrations of dNTPs in tissues of healthy animals and animals with MDS are important for mechanistic studies of mtDNA replication, analysis of disease progression, and the development of therapeutic interventions. Here, we present a sensitive method for the simultaneous analysis of all four dNTPs as well as all four ribonucleoside triphosphates (NTPs) in mouse muscles using hydrophilic interaction liquid chromatography coupled with triple quadrupole mass spectrometry. The simultaneous detection of NTPs allows them to be used as internal standards for the normalization of dNTP concentrations. The method can be applied for measuring dNTP and NTP pools in other tissues and organisms.
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| 23. |
- Thanh Hoan, Nguyen, et al.
(författare)
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Novel Time Series Bagging Based Hybrid Models for Predicting Historical Water Levels in the Mekong Delta Region, Vietnam
- 2022
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Ingår i: CMES - Computer Modeling in Engineering & Sciences. - : Tech Science Press. - 1526-1492 .- 1526-1506. ; 131:3, s. 1431-1449
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Tidskriftsartikel (refereegranskat)abstract
- Water level predictions in the river, lake and delta play an important role in flood management. Every year Mekong River delta of Vietnam is experiencing flood due to heavy monsoon rains and high tides. Land subsidence may also aggravate flooding problems in this area. Therefore, accurate predictions of water levels in this region are very important to forewarn the people and authorities for taking timely adequate remedial measures to prevent losses of life and property. There are so many methods available to predict the water levels based on historical data but nowadays Machine Learning (ML) methods are considered the best tool for accurate prediction. In this study, we have used surface water level data of 18 water level measurement stations of the Mekong River delta from 2000 to 2018 to build novel time-series Bagging based hybrid ML models namely: Bagging (RF), Bagging (SOM) and Bagging (M5P) to predict historical water levels in the study area. Performances of the Bagging-based hybrid models were compared with Reduced Error Pruning Trees (REPT), which is a benchmark ML model. The data of 19 years period was divided into 70:30 ratio for the modeling. The data of the period 1/2000 to 5/2013 (which is about 70% of total data) was used for the training and for the period 5/2013 to 12/2018 (which is about 30% of total data) was used for testing (validating) the models. Performance of the models was evaluated using standard statistical measures: Coefficient of Determination (R2), Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). Results show that the performance of all the developed models is good (R2 > 0.9) for the prediction of water levels in the study area. However, the Bagging-based hybrid models are slightly better than another model such as REPT. Thus, these Bagging-based hybrid time series models can be used for predicting water levels at Mekong data.
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| 24. |
- Tran, Phong, et al.
(författare)
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De novo dNTP production is essential for normal postnatal murine heart development
- 2019
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Ingår i: Journal of Biological Chemistry. - : American Society for Biochemistry and Molecular Biology. - 0021-9258 .- 1083-351X. ; 394:44, s. 15889-15897
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Tidskriftsartikel (refereegranskat)abstract
- The building blocks of DNA, dNTPs, can be produced de novo or can be salvaged from deoxyribonucleosides. However, to what extent the absence of de novo dNTP production can be compensated for by the salvage pathway is unknown. Here, we eliminated de novo dNTP synthesis in the mouse heart and skeletal muscle by inactivating ribonucleotide reductase (RNR), a key enzyme for the de novo production of dNTPs, at embryonic day 13. All other tissues had normal de novo dNTP synthesis and theoretically could supply heart and skeletal muscle with deoxyribonucleosides needed for dNTP production by salvage. We observed that the dNTP and NTP pools in wild-type postnatal hearts are unexpectedly asymmetric, with unusually high dGTP and GTP levels compared with those in whole mouse embryos or murine cell cultures. We found that RNR inactivation in heart led to strongly decreased dGTP and increased dCTP, dTTP, and dATP pools; aberrant DNA replication; defective expression of muscle-specific proteins; progressive heart abnormalities; disturbance of the cardiac conduction system; and lethality between the second and fourth weeks after birth. We conclude that dNTP salvage cannot substitute for de novo dNTP synthesis in the heart and that cardiomyocytes and myocytes initiate DNA replication despite an inadequate dNTP supply. We discuss the possible reasons for the observed asymmetry in dNTP and NTP pools in wildtype hearts.
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| 25. |
- Tran, Phong, et al.
(författare)
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Imbalanced dNTP pools induce mutator and cancer phenotypes in mice
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- The high accuracy of DNA replication is achieved through the nucleotide selectivity of DNA polymerases, polymerase proofreading, and the mismatch repair (MMR) system that act in series. While defects in proofreading and MMR are strongly associated with the development of cancers, decreased nucleotide selectivity due to mutations in replicative DNA polymerases is an uncommon driver of cancer development. Because nucleotide selectivity can also be decreased by imbalanced dNTP pools, we investigated to what extent imbalanced dNTP pools can induce cancers. To this end we developed a mouse model with a mutation in the allosteric specificity site of ribonucleotide reductase, which is responsible for the balanced production of dNTPs. These mice had ~2-fold increased dCTP and dTTP levels and normal dATP and dGTP levels. Despite this mild dNTP pool imbalance, mutant mice had a higher incidence and an earlier onset of cancers, and these were different from the cancers that developed in wild-type controls. Because dNTP pool imbalances can be caused by defects in a plethora of genes, we propose that decreased nucleotide selectivity might be a major factor contributing to the development of spontaneous cancers.
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| 26. |
- Tran, Phong, 1987-
(författare)
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Pathology of dNTP dysregulation
- 2020
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Deoxyribonucleoside triphosphates (dNTPs) are precursors for DNA replication and repair. Mammalian cells have two distinct biosynthesis pathways to supply dNTPs: de novo and salvage pathways. These pathways are intimately coordinated to maintain optimal dNTP concentrations throughout different phases of the cell cycle, and perturbations in the production of dNTPs could lead to increased, decreased, or imbalanced dNTP pools. In yeasts, changes in both the level and balance of dNTPs increase mutation rates and genome instability. In mammals, elevated mutation rates and genome instability predispose to numerous diseases, including cancer. However, the correlation of dNTP changes with pathology has not been well established in mammals. In this thesis, I present how we addressed this issue using three separate mouse models – one with an increased dNTP pool, one with a decreased dNTP pool, and one with an imbalanced dNTP pool. To modulate dNTP levels in the mice, we deleted or mutated either sterile alpha motif and histidine-aspartic domain containing protein 1 (SAMHD1) or ribonucleotide reductase (RNR) proteins, which are involved in the salvage and de novo pathways, respectively. In the first model, mouse embryos without the SAMHD1 gene showed a slight increase in dNTP levels. A similar increase in dNTPs conferred moderately elevated mutation rates in cultured cancer cells. In the second model, we created a mouse strain carrying a modified allosteric specificity site in a subunit of RNR. Embryos with a heterozygous mutation had a mildly imbalanced dNTP pool. Heterozygous mutant mice showed a shorter lifespan and increased incidence and earlier onset of cancer. In the third model, the de novo dNTP production was inactivated in cardiac and skeletal muscles through the deletion of a gene encoding RNR. The hearts of knockout pups showed significant depletion of dNTPs, leading to aberrant DNA replication. In addition, knockout pups developed anatomic and histologic cardiac abnormalities and impaired cardiac conduction systems. As a result, they died between two and four weeks after birth. Taken together, our studies provide the first empirical evidence that both the de novo and salvage pathways are essential to keeping the dNTP concentration at an optimal range to prevent mutagenesis, carcinogenesis, and mortality.
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| 27. |
- Van-Thuoc, Doan, et al.
(författare)
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Poly(3-Hydroxybutyrate-co-3-Hydroxyvalerate) Production by a Moderate Halophile Yangia sp ND199 Using Glycerol as a Carbon Source
- 2015
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Ingår i: Applied Biochemistry and Biotechnology. - : Springer Science and Business Media LLC. - 1559-0291 .- 0273-2289. ; 175:6, s. 3120-3132
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Tidskriftsartikel (refereegranskat)abstract
- Yangia sp. ND199, a moderate halophile isolated from mangrove soil sample in Vietnam, was found to accumulate poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) from unrelated carbon sources in a medium with 4.5 % (w/v) NaCl. Cultivation with glycerol as carbon source and yeast extract as nitrogen source resulted in maximum cell dry weight of 5.7 g/l and PHBV content of 52.8 wt% (containing 2.9 mol% of 3HV) after 40 h. The 3HV content of the PHBV was the highest during initial stages of copolymer production and decreased with increase in the copolymer amount with time, but was not affected by changing the pH of the culture medium. Only homopolymer poly(3-hydroxybutyrate) was synthesized when monosodium glutamate was used as the nitrogen source. Fed-batch cultivation of Yangia sp. ND199 with glycerol and yeast extract gave PHBV content and productivity of 53.2 wt% and 0.44 g/l/h, respectively, which were reduced to 40.6 wt% and 0.25 g/l/h, respectively, with crude glycerol as carbon source. Both the copolymer content and productivity were improved to 56 wt% and 0.61 g/l/h, respectively, by using 1:1 mixture of crude glycerol and high fructose corn syrup. This is the first report of PHBV production by a wild-type halophilic bacterium using glycerol as carbon source.
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| 28. |
- Wanrooij, Paulina H., et al.
(författare)
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Elimination of rNMPs from mitochondrial DNA has no effect on its stability
- 2020
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Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 117:25, s. 14306-14313
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Tidskriftsartikel (refereegranskat)abstract
- Ribonucleotides (rNMPs) incorporated in the nuclear genome are a well-established threat to genome stability and can result in DNA strand breaks when not removed in a timely manner. However, the presence of a certain level of rNMPs is tolerated in mitochondrial DNA (mtDNA) although aberrant mtDNA rNMP content has been identified in disease models. We investigated the effect of incorporated rNMPs on mtDNA stability over the mouse life span and found that the mtDNA rNMP content increased during early life. The rNMP content of mtDNA varied greatly across different tissues and was defined by the rNTP/dNTP ratio of the tissue. Accordingly, mtDNA rNMPs were nearly absent in SAMHD1(-/-) mice that have increased dNTP pools. The near absence of rNMPs did not, however, appreciably affect mtDNA copy number or the levels of mtDNA molecules with deletions or strand breaks in aged animals near the end of their life span. The physiological rNMP load therefore does not contribute to the progressive loss of mtDNA quality that occurs as mice age.
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