bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fabrication of silver-chitosan nanocomposite films and their antibacterial activity
Authors: Susilowati E , Maryani  , Ashadi  , Marwan  
Published: July 2020

AbstractThe silver-chitosan nanocomposite film fabrication was carried out by the preparation of silver nanoparticles using chemical reduction methods assisted with microwave irradiation with chitosan as a reducing agent as well as a stabilizer. Silver nitrate is used as a precursor and NaOH as an accelerator. Silver-chitosan nanocomposite colloids were converted into films by casting techniques at the room temperature. Based on UV-Visible spectra, colloidal nanocomposites show absorption peak at the range of 409-412 nm. Based on TEM images, the silver nanoparticles are spherical shaped and distributed with a diameter of 6-10 nm. Based on FTIR spectra, interactions between silver nanoparticles and chitosan occur in the hydroxyl group (-OH) and amine group (-NH) of the chitosan polymer chain. Based on SEM images, the silver-chitosan nanocomposite films show a compact but rough surface morphology. The increase in tensile strength and decrease in elongation at break of the film was in line with the increase in the concentration of silver nitrate, while the value of the elasticity of the film fluctuates depending on the tensile strength and elongation at break. The increasing concentration of silver nitrate also causes an increase in the degree of swelling. silver-chitosan nanocomposite films showed better antibacterial activity against Escherichia coli than Staphylococcus aureus.
Study of Adsorption-Desorption Au(III) Using Imprinted Ionic Material (SiO2 (RHA-BGS)-TMPDT-Au-Imp)
Authors: Prasetyaningrum F R , Hastuti S , Wahyuningsih S , Martini T 
Published: July 2020

Abstract
Research on the adsorption of desorption of Au (III) metal using imprinted ionic SiO2 (RHA-BGS) -TMPDT-Au-Imp material has been carried out.
In this research, silica source (SiO2) from rice husk ash (RHA) and bagasse (BGS) was modified through imprinted ionic technique. Adsorption studies include variations in concentration and selectivity while desorption studies include time variations. Furthermore, the adsorption and desorption processes were characterized using FTIR. The results of the adsorption process followed the Freundlich isotherm model with an adsorption capacity of 981,672 mg/g. The adsorption selectivity shows that the imprinted ionic material (SiO2(RHA-BGS)-TMPDT-Au-Imp) is more selective than the material without imprinted ionic (SiO2 (RHA-BGS) –TMPDT). The order of selectivity is Au(III)/Zn(II)> Au(III)/Fe(III)> Au(III)//Cu(II). Study of desorption kinetics Au(III) followed the zero order kinetics. The results of the FTIR show that there are still O-H, C-H and -NH groups. This indicates the imprinted ionic material (SiO2(RHA-BGS)-TMPDT-Au-Imp) is not damaged.
The Degree of Lithium (Li) Stability Compared To Calcium (Ca) and Magnesium (Mg) From Low Lithium Grade Brine Water with Addition of Limestone and Oxalic Acid
Authors: Firdiyono F. , Lalasari Latifa Hanum , Tarmizi Ermiziar , Sulistiyono Eko , Andriyah Lia , Arini Tri , Natasha Nadia C. , Yunita Fariza E. 
Published: July 2020

Abstract
The purpose of this study was to investigate whether lithium was precipitated along with the removal of Ca and Mg elements from brine water using limestone and oxalic acid. The first stage was Mg removal by adding CaO at room temperature for 3 hours. The second stage was the Ca removal by adding oxalic acid at a ratio of 2; 3; 4; 5; 10; 15; 20; 30; and 40 ml / 100 ml brine water and pH : 0, 1, and 4 at room temperature for 3 hours. The results showed the most optimal addition of CaO was 20 gr/1 l of brine water with the Mg element can be removed above 99 %, while Li was only reduced by about 1 ppm, and the Ca content only increased by around 28 ppm. The use of oxalic acid will also reduce the amount of lithium besides the Ca removal in the form a precipitate of calcium oxalate. The use of oxalic acid at pH 0 and 4 would reduce the Li content more than at pH 1. At the use of oxalic acid up to 40 ml at pH 1, brine water still contained about 78% Li element.
Anti fouling coating characterization with purified Zirconia from West Kalimantan Zircon Sand for Boiler application
Authors: Lestari Yulinda , Zulfia Anne , Krisnaputra Radhian , Satiti Nareswari Novita , Sulistiyono Eko , Mabruri Efendi 
Published: July 2020

Abstract
Zircon sand is a mineral material for zirconia purification which can be found in Indonesia. Zirconia has various functions, one of the function applied at Boiler high temperatures. The low coefficient of zircon thermal expansion indicates high thermal shock and spalling resistance. In this study, zirconia comes from Kalimantan zircon sand was applied to an anti-fouling coating. The purified zirconia is compared with zircon sand and synthetic zirconia. The purified zirconia yields a 82.48% Zr content, compared to the zircon sand has 70.85% Zr content and 89.43% in synthetic zirconia. The substrate used for coating is ferritic steel. The coating method uses a brush coating then sintered at a temperature of 400°C and 800°C. Coatings that contained purified zirconia have a rougher surface compared to coatings that contained zircon sand and synthetic zirconia. It is because the zirconia powder granules produced have a larger size. The microstructure also shows the surface of the coating with zirconia from the purification has a tenuous structure with large granules. It shows further treatment is needed in the purification of zirconia so that the grain size is homogeneous when applied to the coating.
Dissolution of quartz sand in sodium hydroxide solution for producing amorphous precipitated silica
Authors: Febriana E , Manurung U A B , Prasetyo A B , Handayani M , Muslih E Y , Nugroho F , Sulistiyono E , Firdiyono F 
Published: July 2020

Abstract
This research studied the dissolution of quartz sand in sodium hydroxide solution as an effort to form silica precipitate. The dissolution process was carried out using the leaching method directly at atmospheric pressure. The process variables in this study included the concentration of sodium hydroxide solution, temperature, dissolution time, and stirring rate. The four process variables had a positive influence to enhance silica precipitate formation, The result showed that the extraction rate was still low even though the SiO2 concentration in the starting material was very high. Temperature provided the most significant influence among other process variables. The result exhibited that silica precipitate content was 13.6% obtained in the optimum condition at a temperature of 90 °C with a stirring speed of 800 rpm using a 7.5 M of sodium hydroxide solution.
Pitting Corrosion Resistance of CA6NM and 410 Martensitic Stainless Steels in Various Environments
Authors: Mabruri E , Sigit H M , Anwar M S , Prasetyo M A , Nikitasari A , Fretes A De 
Published: July 2020

AbstractPitting corrosion is an importance phenomena in power generation steam turbine, as it is one of the main causes for blade failure, particularly in the last row of low pressure blading. In this work, the pitting corrosion resistance of the widely used blading alloy of wrought 410 stainless steel and that of the candidate alloy of cast CA6NM stainless steel were investigated. Cyclic polarization measurements for all samples were conducted in simulated solution of thermal and geothermal power plants. The experimental results show that the pitting potentials of the cast CA6NM steel were higher compared to those of the wrought 410 steel in all simulated solution. Both steels exhibited higher pitting potentials in CO2 containing simulated geothermal water than those in the other solutions. These results were correlated with microstructure of the steels observed by Scanning Eectron Microscope (SEM).
A novel method to study the twist dynamics in chiral nematic liquid crystals by texture analysis
Authors: Suryantari R , Flaviana  
Published: July 2020

Abstract
We have experimentally studied the twist dynamics as a function of temperatures in chiral nematic liquid crystals by applying texture analysis to the image data observed by polarized light microscopy. These microscopic textures are analyzed using MATLAB software. The irregularity of texture at different temperatures observed by statistical parameter such as entropy indicate the changes of director orientation. Moreover, the changes in textural as a function of temperatures are useful to investigate the order parameter values of chiral nematic liquid crystals also to predict the behavior of twist dynamics. The order parameter values of the samples at different temperatures are obtained based on images intensity along twist-line using simple calculation then the behavior of twist dynamics are visualized. The study of dynamics of twist mode chiral nematic liquid crystals is important to observe the electro-optic effect in display technology or other applications.
Implementation of a chemotherapy stewardship process
Authors: Hennes Emily R , Reed Michael , Mably Mary , Jared Jason , Bergsbaken Jason J , Deming Dustin , Callander Natalie , O’Regan Ruth 
Published: July 2020

Abstract

Purpose
To design and implement a chemotherapy stewardship process to optimize the location of chemotherapy administration in an effort to decrease the number of inappropriate inpatient anticancer regimen administrations and decrease institutional costs associated with inpatient administration.

Summary
As the costs of anticancer agents continue to rise, it is crucial that multidisciplinary efforts are aimed at managing anticancer medication utilization; this is especially important for high-cost medications, medications whose use requires increased monitoring due to safety concerns, and medications that do not exert effects quickly and, as such, can be more appropriately administered in the outpatient setting. It is imperative that pharmacists play a role in managing chemotherapy medication utilization, as pharmacists provide expertise in formulary management, a vast knowledge of financial impact and reimbursement processes, and clinical knowledge that can help predict the expected effectiveness and adverse effects of each anticancer regimen. Our institution sought to develop and implement a multidisciplinary chemotherapy stewardship program targeting the optimization of site of anticancer agent administration with a goal of decreasing both cost and inappropriate utilization of high-cost, high-risk anticancer agents.

Conclusion
Implementation of a chemotherapy stewardship service may decrease the number of inappropriate inpatient anticancer regimen administrations and decrease inpatient resource use, thereby decreasing costs to institutions. The concept of a chemotherapy stewardship process was well received by multidisciplinary healthcare colleagues, and a collaborative approach should be used to design and implement such processes.
Impact of interoperability of smart infusion pumps and an electronic medical record in critical care
Authors: Joseph Roy , Lee Sang Weon , Anderson Scott V , Morrisette Matthew J 
Published: July 2020

Abstract

Purpose
To describe the benefits of smart infusion pump interoperability with an electronic medical record (EMR) system in an adult intensive care unit (ICU) setting.

Summary
In order to assess the impact of smart infusion pump and EMR interoperability, we observed whether there were changes in the frequency of electronic medication administration record (eMAR) documentation of dose titrations in epinephrine and norepinephrine infusions in the ICU setting. As a secondary endpoint, we examined whether smart pump/EMR interoperability had any impact on the rate of alerts triggered by the dose-error reduction software. Pharmacist satisfaction was measured to determine the impact of smart pump/EMR interoperability on pharmacist workflow. In the preimplementation phase, there were a total of 2,503 administrations of epinephrine and norepinephrine; 13,299 rate changes were documented, for an average of 5.31 documented rate changes per administration. With smart pump interoperability, a total of 13,024 rate changes were documented in association with 1,401 administrations, for an average of 9.29 documented rate changes per administration (a 74.9% increase). A total of 1,526 dose alerts were triggered in association with 76,145 infusions in the preimplementation phase; there were 820 dose alerts associated with 48,758 autoprogammed infusions in the postimplementation phase (absolute difference, –0.32%). ICU pharmacists largely agreed (75% of survey respondents) that the technology provided incremental value in providing patient care.

Conclusion
Interoperability between the smart pump and EMR systems proved beneficial in the administration and monitoring of continuous infusions in the ICU setting. Additionally, ICU pharmacists may be positively impacted by improved clinical data accuracy and operational efficiency.
Demystifying artificial intelligence in pharmacy
Authors: Nelson Scott D , Walsh Colin G , Olsen Casey A , McLaughlin Andrew J , LeGrand Joseph R , Schutz Nick , Lasko Thomas A 
Published: July 2020

AbstractPurposeTo provide pharmacists and other clinicians with a basic understanding of the underlying principles and practical applications of artificial intelligence (AI) in the medication-use process.Summary“Artificial intelligence” is a general term used to describe the theory and development of computer systems to perform tasks that normally would require human cognition, such as perception, language understanding, reasoning, learning, planning, and problem solving. Following the fundamental theorem of informatics, a better term for AI would be “augmented intelligence,” or leveraging the strengths of computers and the strengths of clinicians together to obtain improved outcomes for patients. Understanding the vocabulary of and methods used in AI will help clinicians productively communicate with data scientists to collaborate on developing models that augment patient care. This primer includes discussion of approaches to identifying problems in practice that could benefit from application of AI and those that would not, as well as methods of training, validating, implementing, evaluating, and maintaining AI models. Some key limitations of AI related to the medication-use process are also discussed.ConclusionAs medication-use domain experts, pharmacists play a key role in developing and evaluating AI in healthcare. An understanding of the core concepts of AI is necessary to engage in collaboration with data scientists and critically evaluating its place in patient care, especially as clinical practice continues to evolve and develop.
Ascorbate glutathione-dependent H2O2 scavenging is an important process in axillary bud outgrowth in rosebush
Authors: Porcher Alexis , Guérin Vincent , Montrichard Françoise , Lebrec Anita , Lothier Jérémy , Vian Alain 
Published: July 2020

Abstract

Background and Aims
Branching is an important mechanism of plant shape establishment and the direct consequence of axillary bud outgrowth. Recently, hydrogen peroxide (H2O2) metabolism, known to be involved in plant growth and development, has been proposed to contribute to axillary bud outgrowth. However, the involvement of H2O2 in this process remains unclear.

Methods
We analysed the content of H2O2 during bud outgrowth and characterized its catabolism, both at the transcriptional level and in terms of its enzymatic activities, using RT–qPCR and spectrophotometric methods, respectively. In addition, we used in vitro culture to characterize the effects of H2O2 application and the reduced glutathione (GSH) synthesis inhibitor l-buthionine sulfoximine (BSO) on bud outgrowth in relation to known molecular markers involved in this process.

Key Results
Quiescent buds displayed a high content of H2O2 that declined when bud outgrowth was initiated, as the consequence of an increase in the scavenging activity that is associated with glutathione pathways (ascorbate–glutathione cycle and glutathione biosynthesis); catalase did not appear to be implicated. Modification of bud redox state after the application of H2O2 or BSO prevented axillary bud outgrowth by repressing organogenesis and newly formed axis elongation. Hydrogen peroxide also repressed bud outgrowth-associated marker gene expression.

Conclusions
These results show that high levels of H2O2 in buds that are in a quiescent state prevents bud outgrowth. Induction of ascorbate–glutathione pathway scavenging activities results in a strong decrease in H2O2 content in buds, which finally allows bud outgrowth.
Functional gene networks reveal distinct mechanisms segregating in migraine families
Authors: Rasmussen Andreas H , Kogelman Lisette J A , Kristensen David M , Chalmer Mona Ameri , Olesen Jes , Hansen Thomas Folkmann 
Published: July 2020

Abstract
Migraine is the most common neurological disorder worldwide and it has been shown to have complex polygenic origins with a heritability of estimated 40–70%. Both common and rare genetic variants are believed to underlie the pathophysiology of the prevalent types of migraine, migraine with typical aura and migraine without aura. However, only common variants have been identified so far. Here we identify for the first time a gene module with rare mutations through a systems genetics approach integrating RNA sequencing data from brain and vascular tissues likely to be involved in migraine pathology in combination with whole genome sequencing of 117 migraine families. We found a gene module in the visual cortex, based on single nuclei RNA sequencing data, that had increased rare mutations in the migraine families and replicated this in a second independent cohort of 1930 patients. This module was mainly expressed by interneurons, pyramidal CA1, and pyramidal SS cells, and pathway analysis showed association with hormonal signalling (thyrotropin-releasing hormone receptor and oxytocin receptor signalling pathways), Alzheimer’s disease pathway, serotonin receptor pathway and general heterotrimeric G-protein signalling pathways. Our results demonstrate that rare functional gene variants are strongly implicated in the pathophysiology of migraine. Furthermore, we anticipate that the results can be used to explain the critical mechanisms behind migraine and potentially improving the treatment regime for migraine patients.
Dynamic Frequency Scaling of a Single-Core Processor Using Machine Learning Paradigms
Authors: Thethi Sukhmani K , Kumar Ravi 
Published: July 2020

Abstract
Dynamic frequency scaling (DFS) is one of the most important approaches for on-the-fly power optimization in modern-day processors. Owing to the trend of chip size shrinkage and increasing the complexity of system design, the problem of achieving an efficient DFS depends upon multi-parametric, non-linear optimization. Hence, it becomes extremely important to identify an optimal underclocking frequency on-the-fly, which depends upon numerous parameters that do not share direct relationship amongst each other. This paper proposes a machine learning approach to DFS of a ubiquitous single-core processor. Several performance parameters of the processor were monitored under an application of a number of clocking frequencies. The dataset thus generated was used to train four artificial neural networks (ANNs) viz. generalized regression (GRNN), decision tree classifier, random forest classifier and backpropagation technique. Under changing parametric conditions of the proposed network, the modes were fit to data while running three applications, i.e. 64- and 1024-point fast fourier transform (FFT) and basicmath applications. The performance of all ANNs was found to be promising and good generalization was obtained with all datasets. In the view of optimizing both speed and power of a system, the results indicate towards suitability of trained GRNN for on-chip deployment for implementing DFS.
Considering Fine-Grained and Coarse-Grained Information for Context-Aware Recommendations
Authors: Luo Yiqin , Sun Yanpeng , Chang Liang , Gu Tianlong , Bin Chenzhong , Li Long 
Published: July 2020

AbstractIn context-aware recommendation systems, most existing methods encode users’ preferences by mapping item and category information into the same space, which is just a stack of information. The item and category information contained in the interaction behaviours is not fully utilized. Moreover, since users’ preferences for a candidate item are influenced by the changes in temporal and historical behaviours, it is unreasonable to predict correlations between users and candidates by using users’ fixed features. A fine-grained and coarse-grained information based framework proposed in our paper which considers multi-granularity information of users’ historical behaviours. First, a parallel structure is provided to mine users’ preference information under different granularities. Then, self-attention and attention mechanisms are used to capture the dynamic preferences. Experiment results on two publicly available datasets show that our framework outperforms state-of-the-art methods across the calculated evaluation metrics.
Theorizing News Literacy Behaviors
Authors: Vraga Emily K , Tully Melissa , Maksl Adam , Craft Stephanie , Ashley Seth 
Published: July 2020

AbstractDespite renewed interest in news literacy (NL) as a way to combat mis- and dis-information, existing scholarship is plagued by insufficient theory building and inadequate conceptualization of both “NL” and its application. We address this concern by offering a concise definition of NL and suggest five key knowledge and skill domains that comprise this literacy. We distinguish NL from its application to behaviors that communication scholars have been interested in, including news exposure, verification, and identifying misinformation. We propose an adapted Theory of Planned Behavior (TPB) to include NL in addition to the existing components (attitudes towards the behavior, social norms, perceived behavioral control) when modeling NL Behaviors. We discuss how this model can unite scholars across subfields and propose a research agenda for moving scholarship forward.