A THEORETICAL STUDY ON CHEMICAL BONDING AND INFRARED SPECTRA OF SinM (M = Sc, Y; n = 1-10) CLUSTERS

In this paper, we applied the B3P86 method and DGDZVP basis set to investigate electronic properties and infrared (IR) spectra for SinM (M = Sc, Y; n = 1-10) clusters. The NBO analyses show that electron transfers from the dopant atoms to silicon frame of the SinM clusters. It is remarkable that the Si-M bond is mainly formed by the overlaps of the 3s-AOs and 3p-AOs of Si atoms, and 3d-AOs and 4s-AOs of Sc (or 4d-AOs and AO-5s of Y). The chemical bonds in the SiM and Si2M clusters are dominated by the covalent character including sigma and pi bonds. In addition, the analysis of the IR spectra suggests that the vibrational modes of SinM clusters are delocalized over the whole cluster. Moreover, the high-frequency and strong-intensity modes usually involve the vibrations of the dopant atoms. The results of this work provide fundamental information for experimental studies on transition-metal doped silicon clusters

Machine Learning-Based Digital Twin for Predictive Modeling in Wind Turbines

Wind turbines are one of the primary sources of renewable energy, which leads to a sustainable and efficient energy solution. It does not release any carbon emissions to pollute our planet. The wind farms monitoring and power generation prediction is a complex problem due to the unpredictability of wind speed. Consequently, it limits the decision power of the management team to plan the energy consumption in an effective way. Our proposed model solves this challenge by utilizing a 5G-Next Generation-Radio Access Network (5G-NG-RAN) assisted cloud-based digital twins’ framework to virtually monitor wind turbines and form a predictive model to forecast wind speed and predict the generated power. The developed model is based on Microsoft Azure digital twins infrastructure as a 5-dimensional digital twins platform. The predictive modeling is based on a deep learning approach, temporal convolution network (TCN) followed by a non-parametric k-nearest neighbor (kNN) regression. Predictive modeling has two components. First, it processes the univariate time series data of wind to predict its speed. Secondly, it estimates the power generation for each quarter of the year ranges from one week to a whole month (i.e., medium-term prediction) To evaluate the framework the experiments are performed on onshore wind turbines publicly available datasets. The obtained results confirm the applicability of the proposed framework. Furthermore, the comparative analysis with the existing classical prediction models shows that our designed approach obtained better results. The model can assist the management team to monitor the wind farms remotely as well as estimate the power generation in advance

Clinical Characteristics and Histopathology of Idiopathic Epiretinal Membrane in Vietnam

BACKGROUND: Idiopathic epiretinal membrane (iERM) is an avascular proliferation of different types of cells between the posterior vitreous cortex and the internal limiting membrane. That causes visual impairment including blurry, distortion, scotoma. Many studies of iERM were done to describe the clinical characteristics and investigate the histopathology of this disease. Nonetheless, there has not been a study of iERM histopathology in Vietnam. AIMS: To describe clinical characteristics and histopathological results of idiopathic retinal membrane and the association between them. METHODS: A cross sectional decriptive study of 35 iERMs (33 patients) in Vietnam National Institute of Ophthalmology (VNIO). RESULTS: High morbidity incidence was in group age >50 years (32/35), female gender (26/35), limited movement works (27/35), and high educational levels (28/35). Distortion was the highest (77.14%), scotoma and floater was less frequent (28.5%, 45.7%). Macular edema in all cases and PVD and exudate were high frequent (65.7%, 62.8%). Symptom duration was 8.2 ± 4.7 months, (1-21 months). Mean of central macular thickness was 468.51 ± 97.24 µm (656-274 µm). Six types of cell were detected, including glial cell (35/35), fibroblast (23/35), myofibroblast (23/35), macrophage (13/35), lymphocyte (5/35) and neutrophil (2/35). The number of cell types in one sample ranged from 1-5 types (2.85 ± 1.28 cell types). Number of cell types were correlated to symptom duration (r = 0.47, p = 0.004, Pearson's test) and central macular thickness (r = 0.72, p < 0.001, Pearson's test). CONCLUSION: There were 6 types of cells in iERM. Glial cell was the most frequent cell, inflammatory cells (macrophage, lymphocyte, neutrophil) was also detected. The number of cell types was stastitically correlated to symptom duration and CMT

Network Coding with Multimedia Transmission and Cognitive Networking: An Implementation based on Software-Defined Radio

Network coding (NC) is considered a breakthrough to improve throughput, robustness, and security of wireless networks. Although the theoretical aspects of NC have been extensively investigated, there have been only few experiments with pure NC schematics. This paper presents an implementation of NC under a two-way relay model and extends it to two\ua0non-straightforward scenarios: (i) multimedia transmission with layered coding and multiple-description coding, and (ii) cognitive radio with Vandermonde frequency division multiplexing (VFDM). The implementation is in real time and based on software-defined radio (SDR). The experimental results show that, by combining NC and source coding, we can control the quality of the received multimedia content in an on-demand manner. Whereas in the VFDM-based cognitive radio, the quality of the received content in the primary receiver is low (due to imperfect channel estimation) yet retrievable. Our implementation results serve as a proof for the practicability of network coding in relevant applications

Network Coding with Multimedia Transmission and Cognitive Networking: An Implementation based on Software-Defined Radio

Network coding (NC) is considered a breakthrough to improve throughput, robustness, and security of wireless networks. Although the theoretical aspects of NC have been extensively investigated, there have been only few experiments with pure NC schematics. This paper presents an implementation of NC under a two-way relay model and extends it to two non-straightforward scenarios: (i) multimedia transmission with layered coding and multiple-description coding, and (ii) cognitive radio with Vandermonde frequency division multiplexing (VFDM). The implementation is in real time and based on software-defined radio (SDR). The experimental results show that, by combining NC and source coding, we can control the quality of the received multimedia content in an on-demand manner. Whereas in the VFDM-based cognitive radio, the quality of the received content in the primary receiver is low (due to imperfect channel estimation) yet retrievable. Our implementation results serve as a proof for the practicability of network coding in relevant applications

Synthesized BiVO4 was by the co-precipitation method for Rhodamine B degradation under visible light

Recently, BiVO4 photocatalysts has been received much attention in field of catalysts. Because it can be used to degrade harmful organic catalysts in visible light, irradiation produces CO2, H2O and less harmful organic matter. In this study, we have successfully synthesized a BiVO4 photocatalysts via co-precipitation method in the presence of urea and different calcined temperatures. The survey calcined temperatures as 300°C; 350°C; 400°C and 450°C. The obtained materials were characterized by Scanning electron microscope (SEM) and X-ray diffraction (XRD). The photocatalytic activity was evaluated by the photocatalytic degradation of rhodamine B (RhB) degradation under visible compact Philip lamp (40W) light irradiation. The result indicates that all samples calcined are monoclinic scheelite structure of BiVO4. The BiVO4-350°C sample performed the best in the photodegradation of RhB

Impact assessment of a local seventeen-year initiative on cassava-based soil conservation measure on sloping land as a climate-smart agriculture practice in Van Yen District, Yen Bai Province, Vietnam

Van Yen District in Yen Bai Province represents the general terrain conditions and farming systems of the northern mountainous region of Vietnam. It has suffered land degradation due to soil erosion and nutrient depletion, which in turn led to declined crop yield, and food insecurity. The district experienced these impacts due to unsustainable upland agricultural practices. The Department of Agriculture and Rural Development realized that their previous practices would not leave anything behind for the next generations. This prompted them to launch an agricultural conservation program in 2003 to restore degraded soils, which would improve the production in the farms, and diversify incomes and the household economy of local farmers. Over the 17 years of implementation, the program has introduced six conservation measures that have been well-received and implemented by the farmers of Van Yen. This report assesses the impacts of the 17-year program using the economic, environmental, and social lenses with a focus on the cassava crop, considering the traditional cassava monocrop system (or non-adoption group) and the six conservation measures (or adoption group). The study applied a mixed-methods approach, using semi-questionnaire to collect qualitative information from 488 farmers across six communes and surveys to collect soil samples to assess the levels of soil restoration among certain measures. The study also used the quantitative research findings from two other research studies conducted in Mau Dong Commune to help discuss its findings

Conservation agriculture for a climate-resilient and sustainable upland agriculture: A success story from a seventeen-year local program in northern Vietnam

The brief elaborates on the lessons learned from an impact assessment of a local seventeen-year initiative on cassava-based soil conservation measure on sloping land as a climate-smart agriculture practice in Van Yen District, Yen Bai Province, Vietnam. Focusing on the economic, environmental, and social benefits, the recommendations push for institutional level strategies on how this success story can be replicated in areas with similar biophysical and socio-economic conditions