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Fabrication a sustainable adsorbent nanocellulose-mesoporous hectorite bead for methylene blue adsorption

Case Studies in Chemical and Environmental Engineering 2024年 10卷

作者： Holilah Asranudin El Messaoudi, Noureddine Ulfa, Maria Hamzah, Amir Hamid, Zuratul Ain Abdul Ramadhani, Dini Viandi Suryanegara, Lisman Mahardika, Melbi Melenia, Alvina Tata Pratama, Agus Wedi Prasetyoko, Didik Research Center for Biomass and Bioproducts National Research and Innovation Agency of Indonesia (BRIN) Research Collaboration Center for Nanocellulose BRIN-Andalas University Research Collaboration Center for Biomass and Biorefinery Between BRIN and Universitas Padjadjaran Laboratory of Applied Chemistry and Environment Faculty of Sciences Ibn Zohr University Chemistry Education Study Program Faculty of Teacher Training and Education Sebelas Maret University Deputy for Infrastructure Research and Innovation National Research and Innovation Agency of Indonesia (BRIN) School of Materials & Mineral Resources Engineering Universiti Sains Malaysia Department of Biology Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember Department of Chemistry Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember (ITS) Kampus ITS Sukolilo

In this study, fabrication of mesoporous nanocellulose-hectorite-alginate bead (B-NcH) composites and their application for adsorption of MB from water was carried out. The synthesis of nanocellulose (NC) was conducted from mangosteen waste peel (Garcinia mangostana L.). Garcinia mangostana L. peel had 58.9 ± 0,41 % content of cellulose. NCs was successfully isolated using the acid hydrolysis method. NC from Garcinia mangostana L. peel had a diameter of 24.5 ± 0.2 nm and a length of 381.2 ± 10.4 nm. The superabsorbent was composed of nanocrystalline cellulose, mesoporous hectorite, and alginate. The functional group, phase, and morphology of composite was investigated. The composite with 5 % NC had excellent mechanical strength. The B-NcH5 showed a high adsorption capacity of methylene blue (MB), reaching 98.64 % at an adsorbent dose of 30 mg for 90 min. The presence of hectorite can increase the adsorption ability compared to NCs-alginate. The equilibrium adsorption data followed the Freundlich isotherm;however, the kinetics of adsorption showed the usefulness of adopting the PSO kinetic model. The highest adsorption capacity of B-NcH5 for MB was determined to be 57.59 mg/g. For thermodynamic studies, it was revealed that the adsorption of MB on BNcH-5 is a spontaneous and endothermic process. The removal efficiency was observed in six consecutive cycles, indicating at the favorable reusability of this adsorbent. These results validate the potential use of this B-NcH5 adsorbent for water treatment applications. © 2024

关键词： Adsorption Bead Hectorite Methylene blue Nanocellulose Water treatment

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Extrapolation and option-implied kurtosis in volatility forecasting

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Pacific Basin Finance Journal 2024年 84卷

作者： Pan, Ging-Ginq Shiu, Yung-Ming Wu, Tu-Cheng International Bachelor Degree Program in Finance National Pingtung University Science and Technology 1 Shuefu Road Pingtung Neipu Taiwan Department of Risk Management and Insurance Risk and Insurance Research Center College of Commerce National Chengchi University 64 Sec. 2 Zhi-Nan Road Wen-Shan District Taipei Taiwan Department of Data Science and Analytics I-Shou University 1 Sec. 1 Syuecheng Road Dashu District Kaohsiung Taiwan

Prior studies have employed extrapolation to reduce truncation errors when computing risk-neutral moments. However, extrapolation may have a disadvantage in that it obscures the predictive power of risk-neutral skewness and kurtosis. Our out-of-sample results show that extrapolation does not enhance the predictive power of the volatility forecasting models when risk-neutral volatility, skewness, and kurtosis are included. Under this model specification, extrapolation generates less accurate forecasts and obscures the performance of risk-neutral kurtosis in volatility forecasting. © 2024 Elsevier B.V.

关键词： Extrapolation Risk-neutral kurtosis Risk-neutral skewness Volatility forecasting

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Spin-tunable thermoelectric performance in monolayer chromium pnictides

arXiv

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arXiv 2021年

作者： Muntini, Melania S. Suprayoga, Edi Wella, Sasfan A. Fatimah, Iim Yuwana, Lila Seetawan, Tosawat Cahaya, Adam B. Nugraha, Ahmad R.T. Hasdeo, Eddwi H. Department of Physics Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember Surabaya60111 Indonesia Research Center for Quantum Physics National Research and Innovation Agency Tangerang Selatan15314 Indonesia Center of Excellence on Alternative Energy Research and Development Institution Sakon Nakhon Rajabhat University Sakon Nakhon47000 Thailand Program of Physics Faculty of Science and Technology Sakon Nakhon Rajabhat University Sakon Nakhon47000 Thailand Department of Physics Faculty of Mathematics and Natural Sciences Universitas Indonesia Depok16424 Indonesia Department of Physics and Material Science University of Luxembourg L-1511 Luxembourg

Historically, finding two-dimensional (2D) magnets is well known to be a difficult task due to instability against thermal spin fluctuations. Metals are also normally considered poor thermoelectric (TE) materials. Combining intrinsic magnetism in two dimensions with conducting properties, one may expect to get the worst for thermoelectrics. However, we will show this is not always the case. Here, we investigate spin-dependent TE properties of monolayer chromium pnictides (CrX, where X = P, As, Sb, and Bi) using first-principles calculations of electron- and phonon-energy dispersion, along with Boltzmann transport formalism under energy-dependent relaxation time approximation. All the CrX monolayers are dynamically stable and they also exhibit half metallicity with ferromagnetic ordering. Using the spin-valve setup with antiparallel spin configuration, the half metallicity and ferromagnetism in monolayer CrX enable manipulation of spin degrees of freedom to tune the TE figure of merit (ZT). At optimized chemical potential and operating temperature of 500 K, the maximum ZT values (≈ 0.22, 0.12, and 0.09) with the antiparallel spin-valve setup in CrAs, CrSb, and CrBi improve up to almost twice the original values (ZT ≈ 0.12, 0.08, and 0.05) without the spin-valve configuration. Only in CrP, which is the lightest species and less spin-polarized among CrX, the maximum ZT (≈ 0.34) without the spin-valve configuration is larger than that (≈ 0.19) with the spin-valve one. We also find that, at 500 K, all the CrX monolayers possess exceptional TE power factors of about 0.02-0.08 W/m.K2, which could be one of the best values among 2D conductors. © 2021, CC BY.

关键词： Chromium

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Predicting drug response through tumor deconvolution by cancer cell lines

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Patterns 2024年第4期5卷 100949页

作者： Hsu, Yu-Ching Chiu, Yu-Chiao Lu, Tzu-Pin Hsiao, Tzu-Hung Chen, Yidong Bioinformatics Program Taiwan International Graduate Program National Taiwan University Taipei115 Taiwan Bioinformatics Program Institute of Statistical Science Taiwan International Graduate Program Academia Sinica Taipei115 Taiwan Institute of Health Data Analytics and Statistics Department of Public Health College of Public Health National Taiwan University Taipei100 Taiwan Greehey Children's Cancer Research Institute University of Texas Health San Antonio San AntonioTX78229 United States Department of Medicine School of Medicine University of Pittsburgh PittsburghPA15261 United States UPMC Hillman Cancer Center University of Pittsburgh PittsburghPA15232 United States Department of Medical Research Taichung Veterans General Hospital Taichung40705 Taiwan Department of Population Health Sciences University of Texas Health San Antonio San AntonioTX78229 United States

Large-scale cancer drug sensitivity data have become available for a collection of cancer cell lines, but only limited drug response data from patients are available. Bridging the gap in pharmacogenomics knowledge between in vitro and in vivo datasets remains challenging. In this study, we trained a deep learning model, Scaden-CA, for deconvoluting tumor data into proportions of cancer-type-specific cell lines. Then, we developed a drug response prediction method using the deconvoluted proportions and the drug sensitivity data from cell lines. The Scaden-CA model showed excellent performance in terms of concordance correlation coefficients (>0.9 for model testing) and the correctly deconvoluted rate (>70% across most cancers) for model validation using Cancer Cell Line Encyclopedia (CCLE) bulk RNA data. We applied the model to tumors in The Cancer Genome Atlas (TCGA) dataset and examined associations between predicted cell viability and mutation status or gene expression levels to understand underlying mechanisms of potential value for drug repurposing. © 2024 The Authors

关键词： Tumors

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On the computational Bayesian survival spatial Dengue hemorrhagic fever (DHF) modelling with Fernandez–steel skew normal conditional autoregressive (FSSN CAR) frailty

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AIP Conference Proceedings 2023年第1期2536卷

作者： Dwi Rantini Nur Iriawan Irhamah Musofa Rusli Data Science Technology Study Program Faculty of Advanced Technology and Multidiscipline Universitas Airlangga Surabaya 60115 Indonesia Department of Statistics Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember Surabaya 60111 Indonesia Department of Internal Medicine Faculty of Medicine Universitas Airlangga Surabaya 60115 Indonesia

Generally, infectious disease data has a spatial effect, meaning that areas that are close together affect each other. One of the infectious diseases is dengue hemorrhagic fever (DHF). The recovery time of DHF patients is interesting to study. In this research, DHF data in eastern Surabaya was used. The recovery time of this DHF patient can be modeled using one of the statistical methods, namely survival analysis. This recovery time data follows the Weibull distribution. On the data indicated spatial effect, the conditional autoregressive (CAR) model can be used to express dependencies between adjacent areas. Spatial random effects in the survival model were modeled with Normal CAR, Double-Exponential (DE) CAR, and Fernandez-Steel skew Normal (FSSN) CAR. In this research, Cox regression was used and parameter estimation was performed using the Bayesian analysis with Hamiltonian Monte Carlo (HMC) algorithm using the Stan programming language. Based on the comparison of the Watanabe-Akaike information criterion (WAIC), the spatial random effects on the Weibull Cox regression model are best modeled with the FSSN CAR. This is because the FSSN CAR is able to capture error patterns both symmetrical and asymmetrical, not with Normal CAR and DE CAR which can only capture symmetrical error patterns. In this research, several variables that allegedly affect the recovery rate of DHF patients are given. Then, based on the best model, variables that significantly affect the patient's recovery rate are age, the high schools in last education, housewife in the type of occupation, stadium-II in severity level, fever days before entering the hospital, pulse, temperature, and leukocytes.

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Recent trend of metal promoter role for CO₂ hydrogenation to C₁ and C₂₊ products

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South African Journal of Chemical Engineering 2023年 44卷 14-30页

作者： Sholeha, Novia Amalia Holilah, Holilah Bahruji, Hasliza Ayub, Athirah Widiastuti, Nurul Ediati, Ratna Jalil, Aishah Abdul Ulfa, Maria Masruchin, Nanang Nugraha, Reva Edra Prasetyoko, Didik College of Vocational Studies Bogor Agricultural University (IPB University) Jalan Kumbang No. 14 Bogor 16151 Indonesia Research Center for Biomass and Bioproducts National Research and Innovation Agency of Indonesia (BRIN) Cibinong 16911 Indonesia Department Chemistry Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember Kampus ITS Keputih Surabaya Sukolilo 60111 Indonesia Centre of Advanced Material and Energy Science Universiti Brunei Darussalam Jalan Tungku Link BE 1410 Brunei Darussalam Department of Chemical Engineering Faculty of Chemical and Energy Engineering Universiti Teknologi Malaysia 81310 UTM Skudai Johor Johor Bahru Malaysia Centre of Hydrogen Energy Institute of Future Energy Universiti Teknologi Malaysia Skudai 81310 UTM Skudai Johor Johor Bahru Malaysia Chemistry Education Study Program Faculty of Teacher Training and Education Sebelas Maret University Jl. Ir. Sutami 36A Surakarta 57126 Indonesia Research Collaboration Center for Biomass and Biorefinery between BRIN and Universitas Padjadjaran Jatinangor 45363 Indonesia Department of Chemical Engineering Faculty of Engineering Universitas Pembangunan Nasional “Veteran” Jawa Timur East Java Surabaya 60294 Indonesia

CO2 hydrogenation as sustainable route for generation of value-added carbon feedstock is identified as green pathway for mitigation of greenhouse gasses emission. CO2 methanation is one of the promising solutions, whi... 详细信息

CO₂ hydrogenation as sustainable route for generation of value-added carbon feedstock is identified as green pathway for mitigation of greenhouse gasses emission. CO₂ methanation is one of the promising solutions, which only requires reactions at atmospheric pressure while utilizing metal catalysts to overcome kinetic limitations. Metal catalysts can be promoted to alter reducibities, CO₂ adsorption capacities, and H_2[sbnd]CO₂ dissociation potential. The role of metal promoter such as rare earth elements (Ce, Mn, Co, and La) and alkali and alkali earth metal (Li, Na, Ca, and K) will be discussed within the scope of CO₂ methanation. The aspect of catalysts modification towards hydrogen dissociation potential and surface oxygen vacancy will be emphasized to enhance selectivity for methane. Another pathway for CO₂ hydrogenation is via further conversion into longer chain molecules such as olefin and ethanol. The benefit of metal promoter will be discussed in this review on the effect towards promoting C[sbnd]C coupling reaction for producing longer chain alcohol and light olefin. The strategies to develop active catalysts for the coupling reaction of C[sbnd]C will be emphasized with the promoter introduction. For the hydrogenation of CO₂ to longer chain molecules, the main metal catalysts Ni, Pd, Rh, and Co, and their modification with promoter such as Ga, Cu, and alkali metal Na, K will be discussed. A critical analysis of the CO₂ methanation mechanism and further C[sbnd]C reaction to longer chain molecules will be discussed, particularly the effect of metal promoters to stabilize the intermediate and maneuver the catalytic reaction pathway into the desired products. © 2023 The Author(s)

关键词： C1 products C2+ products CO2 Hydrogenation Metal promoter

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Effect of foliar nutrients application to the growth and yield of Physalis peruviana and Physalis alkekengi

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IOP Conference Series: Earth and Environmental science 2022年第1期978卷

作者： Diana Nurus Sholehah Dini Ermavitalini Miratul Khasanah Edy Setiti Wida Utami Hery Purnobasuki Doctoral Study Program of Mathematics and Natural Science Faculty of Science and Technology Airlangga University Indonesia Study Program of Agroecotechnology Faculty of Agriculture University of Trunojoyo Madura Indonesia Departement of Biology Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember Indonesia Departement of Chemistry Faculty of Science and Technology Airlangga University Indonesia Departement of Biology Faculty of Science and Technology Airlangga University Indonesia

Physalis Sp. is a potential medicinal plant and functional food. The use of appropriate nutrients can gain optimal plant growth and productivity. This study aimed to determine the macro and micronutrients that can provide optimal growth and yield of Physalis sp. This research was conducted at a greenhouse in Bangkalan Madura. A factorial randomized block design with four replications was used in this study. The first factor was the species of Physalis Sp., namely P. peruviana and P. alkekengi. The second factor is nutrition at four levels: a spray of water only as control; foliar application of macronutrients at a dose of 2 g/L; foliar application of micronutrients at a dose of 0,125 g/L; foliar Application of a combination of macronutrients 1 g/L and micronutrients 0,0625 g/L. The data obtained were analyzed using analysis of variance (ANOVA) followed by Least Significant Difference (LSD) at the 5 % level. Nutrition significantly affected growth (plant height, stem diameter, and number of leaves) and yield (number of fruit). The interaction between treatments occurred in the number of fruits. Micronutrients gave the highest number of fruit, both species of Physalis sp.

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Study on structure and morphology of silicon-substituted LiFePO4/C doped material

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AIP Conference Proceedings 2023年第1期2604卷

作者： Fahmi Astuti Vera L. Maghfirohtuzzoimah Sahara H. Intifadhah Pelangi Az-Zahra Muhammad R. Ramadhan Mochamad Zainuri Darminto Darminto Department of Physics Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember Kampus ITS Sukolilo Surabaya 60111 Indonesia Study Program of Physics Faculty of Mathematics and Natural Sciences Republic of Indonesia Defense University Bogor Indonesia

Elemental doping and carbon coating on the electrode are able to increase the battery’s performance to be a good energy storage. In this case, some studies are necessary to confirm the quality of the cathode material, LiFePO4 on the Li-ion based battery material (LIB). Here we report the study of structure and morphology of LiFePO4 by silicon doping at the P-atom atomic position and carbon coating (henceforth called as LFP-Si) utilizing the X-Ray diffractometer, the Fourier-transform infrared technique, and both the scanning and transmission electron microscopy (SEM & TEM), as a preliminary investigation to know the structure and morphology of LiFePO4 after elemental doping and carbon coating. All characterization results are essential for the improvement of the performance of LiFePO4/C doped material.

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SCALE RELIANT INFERENCE

arXiv

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arXiv 2022年

作者： Nixon, Michelle Pistner McGovern, Kyle C. Letourneau, Jeffrey David, Lawrence A. Lazar, Nicole A. Mukherjee, Sayan Silverman, Justin D. College of Information Sciences and Technology The Pennsylvania State University United States Program in Bioinformatics and Genomics The Pennsylvania State University United States Department of Molecular Genetics and Microbiology Duke University United States Department of Statistics The Pennsylvania State University United States Huck Institutes for the Life Sciences The Pennsylvania State University United States Departments of Statistical Science Mathematics Computer Science Biostatistics & Bioinformatics Duke University United States Center for Scalable Data Analytics and Artificial Intelligence University of Leipzig Germany Max Planck Institute for Mathematics in the Natural Sciences Germany Department of Medicine The Pennsylvania State University United States

Many scientific fields, including human gut microbiome science, collect multivariate count data where the sum of the counts is unrelated to the scale of the underlying system being measured (e.g., total microbial load in a subject’s colon). This disconnect complicates downstream analyses such as differential analysis in case-control studies. This article is motivated by a novel study of in vitro human gut microbiome models. Popular tools for analyzing these data led to dramatically elevated rates of both false positives and false negatives. To understand those failures, we provide a formal problem statement that frames these challenges of scale in terms of the classical theory of identifiability. We call this the problem of Scale Reliant Inference (SRI). We use this formulation to prove fundamental limits on SRI in terms of criteria such as consistency and type-I error control. We show that the failures of existing methods stem from a fundamental failure to properly quantify uncertainty in the system scale. We demonstrate that a particular type of Bayesian model called a Bayesian Partially Identified Model (PIMs) can correctly quantify uncertainty in SRI. We introduce Scale Simulation Random Variables (SSRVs) as a flexible and efficient approach to specifying and inferring Bayesian PIMs. In the context of both real and simulated data, we find SSRVs drastically decrease type-I and type-II error rates. © 2022, CC BY.

关键词： Bayesian networks

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Projected Time for the Elimination of Cervical Cancer Under Various Intervention Scenarios: Age-Period-Cohort Macrosimulation Study

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JMIR Public Health and Surveillance 2024年 10卷 e46360页

作者： Chen, Yi-Chu Chen, Yun-Yuan Su, Shih-Yung Jhuang, Jing-Rong Chiang, Chun-Ju Yang, Ya-Wen Lin, Li-Ju Wu, Chao-Chun Lee, Wen-Chung Institute of Epidemiology and Preventive Medicine College of Public Health National Taiwan University Taipei Taiwan Head Office Taiwan Blood Services Foundation Taipei Taiwan Master Program in Statistics National Taiwan University Taipei Taiwan Institute of Statistical Science Academia Sinica Taipei Taiwan Taiwan Cancer Registry Taipei city Taiwan Health Promotion Administration Ministry of Health and Welfare Taipei Taiwan Institute of Health Data Analytics College of Public Health National Taiwan University Taipei Taiwan

BACKGROUND: The World Health Organization aims for the global elimination of cervical cancer, necessitating modeling studies to forecast long-term outcomes. OBJECTIVE: This paper introduces a macrosimulation framework using age-period-cohort modeling and population attributable fractions to predict the timeline for eliminating cervical cancer in Taiwan. METHODS: data for cervical cancer cases from 1997 to 2016 were obtained from the Taiwan Cancer Registry. Future incidence rates under the current approach and various intervention strategies, such as scaled-up screening (cytology based or human papillomavirus [HPV] based) and HPV vaccination, were projected. RESULTS: Our projections indicate that Taiwan could eliminate cervical cancer by 2050 with either 70% compliance in cytology-based or HPV-based screening or 90% HPV vaccination coverage. The years projected for elimination are 2047 and 2035 for cytology-based and HPV-based screening, respectively;2050 for vaccination alone;and 2038 and 2033 for combined screening and vaccination approaches. CONCLUSIONS: The age-period-cohort macrosimulation framework offers a valuable policy analysis tool for cervical cancer control. Our findings can inform strategies in other high-incidence countries, serving as a benchmark for global efforts to eliminate the disease. ©Yi-Chu Chen, Yun-Yuan Chen, Shih-Yung Su, Jing-Rong Jhuang, Chun-Ju Chiang, Ya-Wen Yang, Li-Ju Lin, Chao-Chun Wu, Wen-Chung Lee. Originally published in JMIR Public Health and Surveillance (https://***), 18.04.2024.

关键词： Age-period-cohort model Cancer screening Cervical cancer Cervical screening HPV Human papillomavirus Intervention Macrosimulation Population attributable fraction Public health intervention Women

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