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  • 1
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    Online Resource
    Serum osteoprotegerin level in hemodialysis patients using low‐flux reused dialyzer in relation to atherosclerosis
    Wiley ; 2021
    In:  Journal of Clinical Laboratory Analysis Vol. 35, No. 8 ( 2021-08)
    Details
    In: Journal of Clinical Laboratory Analysis, Wiley, Vol. 35, No. 8 ( 2021-08)
    Abstract: To assess the relation of high serum OPG level and carotid atherosclerosis in maintenance hemodialysis (MHD) patients using low‐flux reused dialyzer. Materials and Methods We examined 209 MHD patients with and without carotid atherosclerosis (83 patients and 126 patients) to establish the relation between OPG and atherosclerosis. Results The proportion of carotid atherosclerosis was 39.7%. The median serum OPG level was 45.3 pmol/L. Serum OPG had a good predicting value for atherosclerosis in MHD patients using low‐flux reused dialyzer (AUC = 0.934, p   〈  0.001, cutoff value = 43.35 pmol/L, Se = 81.3%, Sp = 90.9%). Conclusions In this study, serum OPG had a good predicting value for atherosclerosis in MHD patients using low‐flux reused dialyzer.
    Type of Medium: Online Resource
    ISSN: 0887-8013 , 1098-2825
    URL: Issue
    URL: Article
    DOI: 10.1002/jcla.v35.8
    DOI: 10.1002/jcla.23886
    Language: English
    Publisher: Wiley
    Publication Date: 2021
    detail.hit.zdb_id: 2001635-9
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  • 2
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    Triphenylamine–Thienothiophene Organic Charge‐Transport Molecular Materials: Effect of Substitution Pattern on their Thermal, Photoelectrochemical, and Photovoltaic Properties
    Wiley ; 2018
    In:  Chemistry – An Asian Journal Vol. 13, No. 10 ( 2018-05-18), p. 1302-1311
    Details
    In: Chemistry – An Asian Journal, Wiley, Vol. 13, No. 10 ( 2018-05-18), p. 1302-1311
    Abstract: Two readily accessible thienothiophene–triphenylamine charge‐transport materials have been synthesized by simply varying the substitution pattern of the triphenylamine groups on a central thienothiophene π‐linker. The impact of the substitution pattern on the thermal, photoelectrochemical, and photovoltaic properties of these materials was evaluated and, based on theoretical and experimental studies, we found that the isomer in which the triphenylamine groups were located at the 2,5‐positions of the thienothiophene core ( TT‐2,5‐TPA ) had better π‐conjugation than the 3,6‐isomer ( TT‐3,6‐TPA ). Whilst the thermal, morphological, and hydrophobic properties of the two materials were similar, their optoelectrochemical and photovoltaic properties were noticeably impacted. When applied as hole‐transport materials in hybrid perovskite solar cells, the 2,5‐isomer exhibited a power‐conversion efficiency of 13.6 %, much higher than that of its 3,6‐counterpart (0.7 %) under the same standard conditions.
    Type of Medium: Online Resource
    ISSN: 1861-4728 , 1861-471X
    URL: Issue
    URL: Article
    DOI: 10.1002/asia.v13.10
    DOI: 10.1002/asia.201701790
    Language: English
    Publisher: Wiley
    Publication Date: 2018
    detail.hit.zdb_id: 2233006-9
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  • 3
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    Novel biocomposite from polyamide 11 and jute fibres: the significance of fibre modification with SiO 2 nanoparticles
    Wiley ; 2022
    In:  Polymer International Vol. 71, No. 3 ( 2022-03), p. 255-265
    Details
    In: Polymer International, Wiley, Vol. 71, No. 3 ( 2022-03), p. 255-265
    Abstract: Jute fibres (JFs) and polyamide 11 (PA11) are naturally originated materials that, individually, have been widely employed for the manufacture of biocomposites. However, their simultaneous use in an environmentally friendly JFs/PA11 biocomposite that combines the advantages of both materials has received little attention. Therefore, this study investigated the possible fabrication of a biocomposite based on JFs and PA11. Since the dispersion, adhesion and interfacial interaction between JFs and resin matrix are usually poor, the possibility of improving those characteristics was explored via chemical modification. Accordingly, two modification routes were used: alkali treatment and SiO 2 nanoparticle deposition. Both modified and unmodified fibres were blended with PA11 for biocomposite production. Various techniques including Fourier transform infrared spectroscopy, thermogravimetry, mechanical property analysis and scanning electron microscopy were used to characterize fibre and biocomposite samples. The results indicated that thermal and mechanical stability of JFs were considerably improved as a result of modification. The tensile strength and Young's modulus of unmodified fibres was 303.75 MPa and 12.32 GPa, which then increased to 483.66 MPa and 483.66 GPa, respectively, as a result of SiO 2 nanoparticle deposition on the fibre surface. Because of SiO 2 nanoparticle modification, the interaction and adhesion between JFs and PA11 matrix were improved, which led to increases of 58.3%, 11.7% and 45.9% in tensile strength, impact strength and Young's modulus. The success of this study provides a novel route to produce a complete biocomposite from JFs and PA11, which could become a promising alternative to conventional synthetic polymer composites. © 2021 Society of Industrial Chemistry.
    Type of Medium: Online Resource
    ISSN: 0959-8103 , 1097-0126
    URL: Issue
    URL: Article
    DOI: 10.1002/pi.v71.3
    DOI: 10.1002/pi.6316
    Language: English
    Publisher: Wiley
    Publication Date: 2022
    detail.hit.zdb_id: 2004753-8
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  • 4
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    Building a smart traffic light system based on Internet of Things using ‐calculus
    Wiley ; 2022
    In:  Concurrency and Computation: Practice and Experience Vol. 34, No. 10 ( 2022-05)
    Details
    In: Concurrency and Computation: Practice and Experience, Wiley, Vol. 34, No. 10 ( 2022-05)
    Abstract: Traffic is very terrible in most big cities. These cities need many traffic police to control traffic congestion. They can change the duration of traffic lights to reduce levels of congestion of corners. However, the time changed by them is determined just only the feeling of themselves. Making decisions suitable for current congestion at that moment is not trivial. The resistant questions are how to define the logical time of traffic lights or how is an effect of this corner to the consecutive one. Maybe we need to increase the time of the green light at the next corner because of the traffic jam at this corner. The link between two corners is interaction inside concurrent processes. Besides, some exceptional cases also need to be handled, for instance, ambulances or fire trucks. The green light needs to be turned on when they come, and turn back the red light state later. This article proposes a tentative approach that uses context types, including locations, priorities of cars, velocity, and remaining time (the car comes to the corner) to determine traffic light periods. The context‐aware is applied in the infrastructure of the Internet of Things when transferring information to the corner. Maybe, in the future, the other systems such as Arduino, Raspberry pi, or other embedded systems will be joined in the designs as acting part (turn the traffic lights on/off ) and communicating role (connecting to the Internet via wifi) to control the duration of the traffic lights.
    Type of Medium: Online Resource
    ISSN: 1532-0626 , 1532-0634
    URL: Issue
    URL: Article
    DOI: 10.1002/cpe.v34.10
    DOI: 10.1002/cpe.6731
    RVK:
    SA 4270
    Language: English
    Publisher: Wiley
    Publication Date: 2022
    detail.hit.zdb_id: 2052606-4
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  • 5
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    Risk factors for HIV-1 seropositivity in drug users under 30 years old in Haiphong, Vietnam
    Wiley ; 2001
    In:  Addiction Vol. 96, No. 3 ( 2001-03), p. 405-413
    Details
    In: Addiction, Wiley, Vol. 96, No. 3 ( 2001-03), p. 405-413
    Type of Medium: Online Resource
    ISSN: 0965-2140
    URL: Article
    DOI: 10.1046/j.1360-0443.2001.9634055.x
    Language: English
    Publisher: Wiley
    Publication Date: 2001
    detail.hit.zdb_id: 2002997-4
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  • 6
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    Engineering of ZnO/Graphene Nanocomposite for Enhancing Visible Photocatalytic Ability
    Wiley ; 2022
    In:  physica status solidi (a) Vol. 219, No. 24 ( 2022-12)
    Details
    In: physica status solidi (a), Wiley, Vol. 219, No. 24 ( 2022-12)
    Abstract: Herein, the visible light‐photocatalytic performance of synthesized ZnO/Gr composite materials with different Gr content under various conditions, i.e., pH, dye concentration, and different scavengers (to understand the photocatalytic activity mechanism) is systematically investigated. Photocatalytic performance is evaluated with the degradation of methylene blue (MB) in solution under sunlight irradiation. The presence of graphene (Gr) in the ZnO/Gr composites shows enhanced photocatalytic activity compared to pure ZnO under natural sunlight illumination. The highest photodegradation efficiency of ≈94% when the content of Gr is 1 wt% in comparison to ≈76% for the pure ZnO, corresponding to reaction rate constants of 0.01038 and 0.00615 min −1 , respectively. Compared to recent publications, the degradation efficiency is high with relatively high dye concentration, low catalyst amount, and large solution volume. The enhanced visible light absorption and the reduction of bandgap value are attributed to the enhanced photocatalytic properties of the hybridized composite. Moreover, the investigation of the effect of scavenger substances shows that H 2 O 2 strongly enhanced their photocatalytic ability, suggesting that holes (h + ) contribute as the reactive agent in the photodegradation process.
    Type of Medium: Online Resource
    ISSN: 1862-6300 , 1862-6319
    URL: Issue
    URL: Article
    DOI: 10.1002/pssa.v219.24
    DOI: 10.1002/pssa.202200172
    Language: English
    Publisher: Wiley
    Publication Date: 2022
    detail.hit.zdb_id: 1481091-8
    detail.hit.zdb_id: 208850-2
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  • 7
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    Discovery of Four New Compounds from Macropanax membranifolius and Their Cytotoxic Activity
    Wiley ; 2023
    In:  Chemistry & Biodiversity Vol. 20, No. 9 ( 2023-09)
    Details
    In: Chemistry & Biodiversity, Wiley, Vol. 20, No. 9 ( 2023-09)
    Abstract: A phytochemical investigation of the methanolic extract of the Macropanax membranifolius C.B. Shang leaves led to the isolation of three new flavans, (2 R ,3 R )‐4′ ‐O‐ methylcatechin 5 ‐O‐β‐ D‐glucopyranoside ( 1 ), (2 S ,3 S )‐4′ ‐O‐ methylcatechin 5 ‐O‐β‐ D‐glucopyranoside ( 2 ), (2 S ,3 R )‐4′ ‐O‐ methylcatechin 5 ‐O‐β‐ D‐glucopyranoside ( 3 ), one new triterpene glycoside 3 ‐O‐β‐ D‐xylopyranosyl‐(1→6)‐[ β ‐D‐xylopyranosyl‐(1→2)] ‐β‐ D‐glucopyranosyl‐oleanolic acid 28 ‐O‐β‐ D‐glucopyranoside ( 4 ), together with nine known compounds ( 5 ‐ 13 ). Their chemical structures were elucidated based on HR‐ESI‐MS, NMR spectroscopic data. The absolute configurations of compounds 1 – 3 were established by electronic circular dichroism (ECD) spectra. At concentration of 20 μM, compounds 1 – 13 showed the percentages of dead cell in the range of 2.14 % to 33.61 % against KB, HepG2, HL60, P388, HT29, and MCF7 cancerous cell lines by SRB assay.
    Type of Medium: Online Resource
    ISSN: 1612-1872 , 1612-1880
    URL: Issue
    URL: Article
    DOI: 10.1002/cbdv.v20.9
    DOI: 10.1002/cbdv.202301090
    Language: English
    Publisher: Wiley
    Publication Date: 2023
    detail.hit.zdb_id: 2139001-0
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  • 8
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    Landslide susceptibility prediction using machine learning and remote sensing: Case study in Thua Thien Hue province, Vietnam
    Wiley ; 2023
    In:  Geological Journal
    Details
    In: Geological Journal, Wiley
    Abstract: Landslides lead to widespread devastation and significant loss of life in mountainous regions around the world. Susceptibility assessments can provide critical data to help decision‐makers, for example, local authorities and other organizations, mitigating the landslide risk, although the accuracy of existing studies needs to be improved. This study aims to assess landslide susceptibility in the Thua Thien Hue province of Vietnam using deep neural networks (DNNs) and swarm‐based optimization algorithms, namely Adam, stochastic gradient descent (SGD), Artificial Rabbits Optimization (ARO), Tuna Swarm Optimization (TSO), Sand Cat Swarm Optimization (SCSO), Honey Badger Algorithm (HBA), Marine Predators Algorithm (MPA) and Particle Swarm Optimization (PSO). The locations of 945 landslides occurring between 2012 and 2022, along with 14 conditioning factors, were used as input data to build the DNN and DNN‐hybrid models. The performance of the proposed models was evaluated using the statistical indices receiver operating characteristic curve, area under the curve (AUC), root mean square error, mean absolute error (MAE), R 2 and accuracy. All proposed models had a high accuracy of prediction. The DNN‐MPA model had the highest AUC value (0.95), followed by DNN‐HBA (0.95), DNN‐ARO (0.95), DNN‐Adam (0.95), DNN‐SGD (0.95), DNN‐TSO (0.93), DNN‐PSO (0.9) and finally DNN‐SCSO (0.83). High‐precision models have identified that the majority of the western region of Thua Thien Hue province is very highly susceptible to landslides. Models like the aforementioned ones can support decision‐makers in updating large‐scale sustainable land‐use strategies.
    Type of Medium: Online Resource
    ISSN: 0072-1050 , 1099-1034
    URL: Article
    DOI: 10.1002/gj.4885
    Language: English
    Publisher: Wiley
    Publication Date: 2023
    detail.hit.zdb_id: 1479201-1
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  • 9
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    Automatic Detection of Meniscus Tears Using Backbone Convolutional Neural Networks on Knee MRI
    Wiley ; 2023
    In:  Journal of Magnetic Resonance Imaging Vol. 57, No. 3 ( 2023-03), p. 740-749
    Details
    In: Journal of Magnetic Resonance Imaging, Wiley, Vol. 57, No. 3 ( 2023-03), p. 740-749
    Abstract: Timely diagnosis of meniscus injuries is key for preventing knee joint dysfunction and improving patient outcomes because it decreases morbidity and facilitates treatment planning. Purpose To train and evaluate a deep learning model for automated detection of meniscus tears on knee magnetic resonance imaging (MRI). Study type Bicentric retrospective study. Subjects In total, 584 knee MRI studies, divided among training ( n  = 234), testing ( n  = 200), and external validation ( n  = 150) data sets, were used in this study. The public data set MRNet was used as a second external validation data set to evaluate the performance of the model. Sequence A 3 T, coronal, and sagittal images from T1‐weighted proton density (PD) fast spin‐echo (FSE) with fat saturation and T2‐weighted FSE with fat saturation sequences. Assessment The detection system for meniscus tear was based on the improved YOLOv4 model with Darknet‐53 as the backbone. The performance of the model was also compared with that of three radiologists of varying levels of experience. The determination of the presence of a meniscus tear from surgery reports was used as the ground truth for the images. Statistical Tests Sensitivity, specificity, prevalence, positive predictive value, negative predictive value, accuracy, and receiver operating characteristic curve were used to evaluate the performance of the detection model. Two‐way analysis of variance, Wilcoxon signed‐rank test, and Tukey's multiple tests were used to evaluate differences in performance between the model and radiologists. Results The overall accuracies for detecting meniscus tears using our model on the internal testing, internal validation, and external validation data sets were 95.4%, 95.8%, and 78.8%, respectively. One radiologist had significantly lower performance than our model in detecting meniscal tears (accuracy: 0.9025 ± 0.093 vs. 0.9580 ± 0.025). Data Conclusion The proposed model had high sensitivity, specificity, and accuracy for detecting meniscus tears on knee MRIs. Evidence Level 3 Technical Efficacy Stage 2
    Type of Medium: Online Resource
    ISSN: 1053-1807 , 1522-2586
    URL: Issue
    URL: Article
    DOI: 10.1002/jmri.v57.3
    DOI: 10.1002/jmri.28284
    Language: English
    Publisher: Wiley
    Publication Date: 2023
    detail.hit.zdb_id: 1497154-9
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  • 10
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    Swarm‐based optimizer for convolutional neural network: An application for flood susceptibility mapping
    Wiley ; 2021
    In:  Transactions in GIS Vol. 25, No. 2 ( 2021-04), p. 1009-1026
    Details
    In: Transactions in GIS, Wiley, Vol. 25, No. 2 ( 2021-04), p. 1009-1026
    Abstract: This article investigates the use of the galactic swarm optimization algorithm in searching for parameters of a convolutional neural network for flood susceptibility mapping. Ha Giang province, the mountainous area of Vietnam, was chosen as a case study because of the frequent occurrence of floods. From this study area, 11 predictor variables and historical flood locations were selected to build up the training datasets, in which each sample is prepared in the 3D form of (height × width × channels or variables) = (5 × 5 × 11), (7 × 7 × 11), and (9 × 9 × 11), respectively for three experiments. The model performance was assessed by root mean square error, area under the receiver operating characteristic (AUC), and overall accuracy (OA). The results showed that the examined model significantly improved the classification accuracies: OA = 83.093, AUC = 0.917; OA = 83.726, AUC = 0.923; and OA = 82.791, AUC = 0.908 for the three training datasets in comparison to benchmarked classifiers, and this model can be considered as an alternative solution for flood susceptibility mapping.
    Type of Medium: Online Resource
    ISSN: 1361-1682 , 1467-9671
    URL: Issue
    URL: Article
    DOI: 10.1111/tgis.v25.2
    DOI: 10.1111/tgis.12715
    Language: English
    Publisher: Wiley
    Publication Date: 2021
    detail.hit.zdb_id: 2035222-0
    SSG: 14
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