Mesoporous molecular sieve-based materials for catalytic oxidation of VOC: A review

Tang, Xiaolong; Yi, Honghong; Jiang, Shanxue; Yu, Qingjun; Xie, Xizhou; Zhuang, Ruijie

doi:10.1016/j.jes.2021.11.014

Cited by 78 publications

(20 citation statements)

References 105 publications

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“…Many clinical predictors influence gastric cancer. In the reviewed studies, after doing feature ranking, the variables such as age, 6,35,48,49 gender, 36,47,50 body mass index, 6,47,50 Karnofsky performance scale, 8,48,51 TNM stage, 36,47-50 tumor grade, 7,8,35,47-50 tumor size, 6,7,47,49-51 tumor location, 6,7,35,36,48,49 lymphovascular invasion, 7,8,47,49,50 active and timely treatment, 7,8,36 type of treatment, 35,49 disease stage and severity, 6,8,35,36,48,49 and weight loss 36,47,49 were determined as the most important risk factors affecting gastric cancer survival outcome. Similarly, in our study, feature selection analysis was performed to rank the important set of variables.…”

Section: Discussionmentioning

confidence: 99%

“…Many clinical predictors influence gastric cancer. In the reviewed studies, after doing feature ranking, the variables such as age, 6,35,48,49 gender, 36,47,50 body mass index, 6,47,50 Karnofsky performance scale, 8,48,51 TNM stage, 36,[47][48][49][50] tumor grade, 7,8,35,[47][48][49][50] tumor size, 6,7,47,[49][50][51] tumor location, 6,7,35,36,48,49 lymphovascular invasion, 7,8,47,49,50 active and timely treatment, 7,8,36 type of treatment, 35,49 disease stage and severity, 6,8,…”

Section: 037mentioning

confidence: 99%

“…5 The treatment of tumors depends largely on the prognosis judgment that strongly rests on the phase, in which it is detected. 6,7 The 5-year relative survival rate is up to 70% for lesions in the early stages and 4% for lesions in the advanced stages. 6,8,9 Survival often refers to the likelihood, by which a patient will live 60 months after being diagnosed with cancer.…”

Section: Introductionmentioning

confidence: 99%

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Design and Development of an Intelligent System for Predicting 5-Year Survival in Gastric Cancer

Afrash

Yazdani

Kazemi-Arpanahi³

2022

Clin Med Insights Oncol

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Background: Gastric cancer remains one of the leading causes of worldwide cancer-specific deaths. Accurately predicting the survival likelihood of gastric cancer patients can inform caregivers to boost patient prognostication and choose the best possible treatment path. This study intends to develop an intelligent system based on machine learning (ML) algorithms for predicting the 5-year survival status in gastric cancer patients. Methods: A data set that includes the records of 974 gastric cancer patients retrospectively was used. First, the most important predictors were recognized using the Boruta feature selection algorithm. Five classifiers, including J48 decision tree (DT), support vector machine (SVM) with radial basic function (RBF) kernel, bootstrap aggregating (Bagging), hist gradient boosting (HGB), and adaptive boosting (AdaBoost), were trained for predicting gastric cancer survival. The performance of the used techniques was evaluated with specificity, sensitivity, likelihood ratio, and total accuracy. Finally, the system was developed according to the best model. Results: The stage, position, and size of tumor were selected as the 3 top predictors for gastric cancer survival. Among the 6 selected ML algorithms, the HGB classifier with the mean accuracy, mean specificity, mean sensitivity, mean area under the curve, and mean F1-score of 88.37%, 86.24%, 89.72%, 88.11%, and 89.91%, respectively, gained the best performance. Conclusions: The ML models can accurately predict the 5-year survival and potentially act as a customized recommender for decision-making in gastric cancer patients. The developed system in our study can improve the quality of treatment, patient safety, and survival rates; it may guide prescribing more personalized medicine.

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Section: Discussionmentioning

confidence: 99%

“…Many clinical predictors influence gastric cancer. In the reviewed studies, after doing feature ranking, the variables such as age, 6,35,48,49 gender, 36,47,50 body mass index, 6,47,50 Karnofsky performance scale, 8,48,51 TNM stage, 36,[47][48][49][50] tumor grade, 7,8,35,[47][48][49][50] tumor size, 6,7,47,[49][50][51] tumor location, 6,7,35,36,48,49 lymphovascular invasion, 7,8,47,49,50 active and timely treatment, 7,8,36 type of treatment, 35,49 disease stage and severity, 6,8,…”

Section: 037mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Design and Development of an Intelligent System for Predicting 5-Year Survival in Gastric Cancer

Afrash

Yazdani

Kazemi-Arpanahi³

2022

Clin Med Insights Oncol

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“…Therefore, in this paper, the Ti-SBA-15 composite was prepared by the direct synthesized method with using a TiO2 nano-powder source. In order to enhance the extended range of the spectrum of TiO2 a number of transition metal nanoparticles (Cu, Fe, Co, Cr, Ni) were chosen for doping on the surface of the TiO2/SBA-15 because transition metals have good electron changeability enhancing catalytic activity, anti-poisoning property, longevity, regeneration, and low cost [26]. The composition, morphology and optical properties of synthesized photocatalysts are characterized by XRD, SEM-EDX, XRF, UV-DRS, and N2 adsorption-desorption isotherms.…”

Section: Introductionmentioning

confidence: 99%

The effect of metal-titania interaction on photodegradation in SBA-15-supported metal-titania photocatalysts

Göl

Akbay

2023

CI&CEQ

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Several transition metals (Fe, Cu, Ni, Cr, and Co) were inserted into the Ti-SBA-15 using two-step synthesis methods. XRD, SEM-EDX, N2 adsorption-desorption isotherms, XRF, and UV-DRS analysis were used for characterizations. The results confirm the preservation of an ordered mesoporous structure and well-dispersed Ti-metal, and enhanced the absorption of light compared with Ti-SBA-15. The photocatalytic performances were evaluated in the degradation of methylene blue under UV light. The results show that the Co-Ti-SBA-15 exhibited the highest photocatalytic activity among the prepared photocatalysts for the degradation of methylene blue. The significant activity increase might be attributed to the increased reactant adsorption by the mesoporous structure of SBA-15, the good distribution of TiO2 in the pores of SBA-15, and the increased electron transfer mobility due to metal doping. In addition to efficiency, Co-Ti-SBA-15 is a suitable catalyst for dye degradation, exhibiting good stability in methylene blue degradation over five photocatalytic runs without any deviation of the structure.

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“…Among them, the adsorption method is widely used in the field of VOC removal due to the advantages of reusability and high recovery rate. The commonly used VOC adsorbents mainly include zeolite molecular sieves, 10,11 activated carbon, 12 super cross-linked polymerization resin, etc. 13 In recent years, porous metal−organic frameworks with rich porous structures have received much attention.…”

Section: ■ Introductionmentioning

confidence: 99%

Experimental and Simulation Studies of the Adsorption of Methylbenzene by Fe(III)-Doped NU-1000 (Zr)

Yang

Gao

Wang

et al. 2022

ACS Appl. Mater. Interfaces

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Metal–organic framework (MOF) materials, NU-1000(Zr) and Fe(III)-doped NU-1000(Zr), were prepared through the hydrothermal method and used to remove methylbenzene in this work. The pore structure, crystal structure, adsorption capacity, adsorption heat, and adsorption density of Fe(III)-doped NU-1000(Zr) were analyzed based on the experimental and Giant Canonical Monte Carlo (GCMC) simulation methods. The results show that Fe3+ has a uniform distribution and a stable structure after NU-1000(Zr) was modified with Fe3+. The adsorption–penetration experiments of NU-1000 doped with different concentrations of Fe3+ have shown that the adsorption capacity of methylbenzene on the material surface is up to 231 mg g–1 at Fe/Zr = 0.1, which is due to the less doping of Fe elements and more defective sites in the structure. The GCMC simulation shows that NU-1000(Zr) and Fe(III)-NU-1000(Zr) adsorbed methylbenzene through π–π interaction, and the adsorption effect is good and close to the experimental result. The conclusions of this paper provide important support for the modification of MOF materials and the removal of methylbenzene.

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Mesoporous molecular sieve-based materials for catalytic oxidation of VOC: A review

Cited by 78 publications

References 105 publications

Design and Development of an Intelligent System for Predicting 5-Year Survival in Gastric Cancer

Design and Development of an Intelligent System for Predicting 5-Year Survival in Gastric Cancer

The effect of metal-titania interaction on photodegradation in SBA-15-supported metal-titania photocatalysts

Experimental and Simulation Studies of the Adsorption of Methylbenzene by Fe(III)-Doped NU-1000 (Zr)

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