compound model
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Catalysts ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 1406
Author(s):  
Luis Alejandro Martínez-Chávez ◽  
Eric Mauricio Rivera-Muñoz ◽  
Rodrigo Rafael Velázquez-Castillo ◽  
Luis Escobar-Alarcón ◽  
Karen Esquivel

Titanium dioxide (TiO2) is widely used, studied, and synthesized using different methodologies. By a modification of the material, it can be applied to wastewater treatment. A combined sputtering-laser ablation setup was used to deposit TiO2 thin films modified, individually and simultaneously, with gold (Au) and silver (Ag). To investigate the effect of the metal incorporation in titanium and its impact on the photocatalytic activity, with dye discoloration as a pollutant compound model, the deposited films were characterized by UV–Vis, photoluminescence, and Raman spectroscopies, as well as by parallel beam X-ray diffraction. The results showed that films with different Au and Ag loads, and an 18 nm average crystallite size, were obtained. These metals have an essential effect on the deposited film’s compositional, structural, and optical properties, directly reflected in its photocatalytic activity. The photocatalytic test results using UV-Vis showed that, after 1 h of applying a 4.8 V electric voltage, a discoloration of up to 80% of malachite green (MG) was achieved, using ultraviolet (UV) light.


2021 ◽  
Vol 6 (2) ◽  
pp. 236-251
Author(s):  
Nadia Azahro Choirunisa ◽  
Tita Karlita ◽  
Rengga Asmara

Kucing merupakan hewan yang sangat popular di dunia. Jumlah dari ras kucing di dunia hanya sekitar 1% saja, sehingga didominasi oleh ras campuran maupun kucing domestik. Namun demikian, ada begitu banyak jenis ras kucing di dunia, sehingga terkadang sulit untuk mengidentifikasinya. Oleh karena itu, dibutuhkan sistem yang dapat mengenali jenis-jenis ras kucing. Dalam penelitian ini, penulis menggunakan salah satu metode deep learning yang dapat mengenali dan mengklasifikasikan suatu objek, yaitu Neural Convolutional Network (CNN). Penulis menggunakan 9 jenis ras kucing yang berbeda berisi 2700 gambar. Dalam pengujiannya, penulis menggunakan arsitektur EfficientNet-B0. Model paling optimal dari pengujian yang dilakukan terhadap 180 gambar kucing memperoleh tingkat akurasi sebesar 95%.   Kata Kunci : Deep Learning, Convolutional Neural Network (CNN) , Ras kucing, EfficientNet-B0.


Genes ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1215
Author(s):  
Yichen Li ◽  
Zhuo Xing ◽  
Tao Yu ◽  
Annie Pao ◽  
Marcel Daadi ◽  
...  

Down syndrome (DS) is one of the most complex genetic disorders in humans and a leading genetic cause of developmental delays and intellectual disabilities. The mouse remains an essential model organism in DS research because human chromosome 21 (Hsa21) is orthologously conserved with three regions in the mouse genome. Recent studies have revealed complex interactions among different triplicated genomic regions and Hsa21 gene orthologs that underlie major DS phenotypes. Because we do not know conclusively which triplicated genes are indispensable in such interactions for a specific phenotype, it is desirable that all evolutionarily conserved Hsa21 gene orthologs are triplicated in a complete model. For this reason, the Dp(10)1Yey/+;Dp(16)1Yey/+;Dp(17)1Yey/+ mouse is the most complete model of DS to reflect gene dosage effects because it is the only mutant triplicated for all Hsa21 orthologous regions. Recently, several groups have expressed concerns that efforts needed to generate the triple compound model would be so overwhelming that it may be impractical to take advantage of its unique strength. To alleviate these concerns, we developed a strategy to drastically improve the efficiency of generating the triple compound model with the aid of a targeted coat color, and the results confirmed that the mutant mice generated via this approach exhibited cognitive deficits.


2021 ◽  
Vol 292 ◽  
pp. 02030
Author(s):  
Jie Gao

The stock plays a vital role in economic life, and the economic development of enterprises can be measured by the development and change of stocks. In this paper, the closing price of Ping An stock in China from 2017 to 2019 is selected as the time series empirical analysis data, and the ARIMA-GARCH model is established to predict the law and trend of the stock price change. The results show that the compound model can fit the fluctuation law well, and reasonably predict the short-term fluctuation trend.


2020 ◽  
Vol 17 (2) ◽  
pp. 293-303
Author(s):  
Nur Hilal A Syahrir ◽  
Sumarheni Sumarheni ◽  
Supri Bin Hj Amir ◽  
Hedi Kuswanto

Jamu is one of Indonesia's cultural heritage, which consists of several plants that have been practiced for centuries in Indonesian society to maintain health and treat diseases. One of the scientification efforts of Jamu to reveal its mechanism is to predict the target-protein of the active ingredients of the Jamu. In this study, the prediction of the target compound for Jamu was carried out using a supervised learning approach involving conventional medicinal compounds as training data. The method used in this study is the closest profile method adopted from the nearest neighbor algorithm. This method is implemented in drug compound data to construct a learning model. The AUC value for measuring performance of the three implemented models is 0.62 for the fixed compound model, 0.78 for the fixed target model, and 0.83 for the mixed model. The fixed compound model is then used to construct a prediction model on the herbal medicine data with an optimal threshold value of 0.91. The model produced 10 potential compounds in the herbal formula and its 44 unique protein targets. Even though it has many limitations in obtaining a good performance, the closest profile method can be used to predict the target of the herbal compound whose target is not yet known.


Author(s):  
Tareef Fadhil Raham

Back ground: BCG have heterogeneous immunity to certain pathogens other than Mycobacterium tuberculosis effect. At early times during COVID-19 pandemic heterogeneous immunity towards (SARS-CoV-2), was hypothesized and statistical correlation between of BCG vaccination practices and COVID-19 mortality variances among countries was statistically proved . These studies was criticized because of low evidence of such studies and possible confounding factors. For that reason this study was designed to look for impact of duration of cessation of BCG programs on Covid-19 mortality looking for the hypotheses by different design and looking forward to support previous studies. Methods: Total number of studied group is 14 countries which has stopped BCG vaccination programs. Through applying stem-leaf plot for exploring data screening behavior concerning Covid-19 Mortality for obsolescence duration of cessation of mass BCG vaccination programs, as well as (nonlinear regression of compound model) for predicted shape behavior for that group. Results: Slope value shows highly significant effectiveness of obsolescence of cessation of mass BCG vaccination programs on Covid -19 mortality at P-value<0.000. Obsolescence of duration of cessation of mass BCG vaccination programs has strongly negatively associated with Covid-19 mortality in countries which stopped BCG vaccination programs. Conclusion: The longer the cessation duration of BCG programs, the higher the Covid-19 mortality is, and vice versa.


Author(s):  
Tareef Fadhil Raham

AbstractBack groundLatent TB disease reflect a state of persistent immune response to stimulation by Mycobacterium tuberculois. TB infection lead to latent TB disease in 90-95 % while 5-10 % of individuals develop active TB disease when compared to BCG, BCG is 60% effective against the development of active TB. Studies done to test association of BCG with covid-19 morbidity and mortality and it was thought that BCG have preventive effects due to presumed non specific anti viral effects in this study we test association between prevalent of TB which reflects about 90-95 % of corresponding latent TB infection with covid 19 mortality.Materials and methodscountries divided into 5 groups according to BCG following status: No vaccination at all no previous BCG group, no current but had BCG in past (one or more), 1 current BCG with previous booster (s), just 1 BCG now no previous booster (s) and more than 1 BCG setting now. covid-19 deaths taken as it is on these are tested against TB prevalence 2018.ResultsSlop values have significant influences between TB prevalence and covid-19 deaths among all tested groups and are reversed in just 1 BCG now no previous booster (s) groupP<0.01 coefficient (0.30751),1 current BCG with previous booster (s) P<0.01 coefficient (0.63662), and more than 1 BCG setting now group P<0.05 with coefficient of (0.61580). While no vaccination at all no previous BCG group shows Compound model linear regression P<0.05 coefficient (97.45%)and No current but had BCG in past (one or more) group shows Cubic model P<0.01, coefficient (66.098%)The overall slope value is highly significant and reverse influence at P<0.01, as well as highly significant relationship coefficient (0.36749).The linear regression model obtained in logarithmic mode for all tested sample and being inverse in countries with more than 1 BCG setting at this time and countries with 1 current BCG with previous booster (s) furthermore linear regression model is logarithmic in countries with just 1 BCG now and no previous booster (s).ConclusionTB prevalence is strongly associated with covid-19 mortality and being more sever in absence of BCG vaccine.RecommendationsEarly interventions might be considered based on the supportive evidence at this timewhich include BCG vaccination, review of current latent TB programs.


Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2377
Author(s):  
Mingyue Ding ◽  
Yachao Li ◽  
Yinghui Quan ◽  
Liang Guo ◽  
Mengdao Xing

The reconstruction of sea clutter plays an important role in target detection and recognition in a maritime environment. Reproducing the temporal and spatial correlations of real data simultaneously is always a problem in the reconstruction of sea clutter due to the complex coupling between them. In this paper, the spatial–temporal correlated proportional method (STCPM), based on a compound model, is proposed to reconstruct K-distributed sea clutter with correlation characteristics obtained from the real data. The texture component with spatial–temporal correlation is generated by the proportional method and the speckle component with temporal correlation is generated by matrix transformation. Compared with previous methods, the biggest innovation of the STCPM is that it can more accurately generate K-distributed sea clutter with both temporal and spatial correlations. The comparison of the reconstructed and real data demonstrates that the method can reproduce the characteristics of real sea clutter well.


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