bluuebunny/crossref_metadata_2025_split huggingface dataset:
Human Factors and Sociotechnical Issues
Authors: Pelayo Sylvia , Senathirajah Yalini ,   Section Editors for the IMIA Yearbook Section on Human Factors and Organizational Issues
Published: August 2019

Objective: To summarize significant research contributions on human factors (HF) and organizational issues in medical informatics published in 2018.
Methods: An extensive search using PubMed/Medline and Web of Science® was conducted to identify the scientific contributions published in 2018 that address human factors and organizational issues in medical informatics. The selection process comprised three steps: (i) 15 candidate best papers were first selected by the two section editors, (ii) external reviewers from internationally renowned research teams reviewed each candidate best paper, and (iii) the final selection of four best papers was conducted by the editorial board of the Yearbook.
Results: The four selected best papers are excellent contributions to the HF literature: they show the added value of HF studies by providing nice illustrated and rigorous interventions.
Conclusion: HF interventions are known to have great potential to contribute to efficient HIT design, but the interventions still face challenges in successfully demonstrating their value to the main stakeholders of the healthcare domain. There is a need to strengthen the demand for high-quality HF studies by increasing awareness among powerful stakeholders of the value of high-quality HF studies.
Formal Medical Knowledge Representation Supports Deep Learning Algorithms, Bioinformatics Pipelines, Genomics Data Analysis, and Big Data Processes
Authors: Dhombres Ferdinand , Charlet Jean ,   Section Editors for the IMIA Yearbook Section on Knowledge Representation and Management
Published: August 2019

Objective: To select, present, and summarize the best papers published in 2018 in the field of Knowledge Representation and Management (KRM).
Methods: A comprehensive and standardized review of the medical informatics literature was performed to select the most interesting papers published in 2018 in KRM, based on PubMed and ISI Web Of Knowledge queries.
Results: Four best papers were selected among the 962 publications retrieved following the Yearbook review process. The research areas in 2018 were mainly related to the ontology-based data integration for phenotype-genotype association mining, the design of ontologies and their application, and the semantic annotation of clinical texts.
Conclusion: In the KRM selection for 2018, research on semantic representations demonstrated their added value for enhanced deep learning approaches in text mining and for designing novel bioinformatics pipelines based on graph databases. In addition, the ontology structure can enrich the analyses of whole genome expression data. Finally, semantic representations demonstrated promising results to process phenotypic big data.
Artificial Intelligence for Surveillance in Public Health
Authors: Thiébaut Rodolphe , Cossin Sébastien ,   Section Editors for the IMIA Yearbook Section on Public Health and Epidemiology Informatics
Published: August 2019

Objectives: To introduce and summarize current research in the field of Public Health and Epidemiology Informatics.
Methods: The 2018 literature concerning public health and epidemiology informatics was searched in PubMed and Web of Science, and the returned references were reviewed by the two section editors to select 15 candidate best papers. These papers were then peer-reviewed by external reviewers to give the editorial team an enlightened selection of the best papers.
Results: Among the 805 references retrieved from PubMed and Web of Science, three were finally selected as best papers. All three papers are about surveillance using digital tools. One study is about the surveillance of flu, another about emerging animal infectious diseases and the last one is about foodborne illness. The sources of information are Google news, Twitter, and Yelp restaurant reviews. Machine learning approaches are most often used to detect signals.
Conclusions: Surveillance is a central topic in public health informatics with the growing use of machine learning approaches in regards of the size and complexity of data. The evaluation of the approaches developed remains a serious challenge.
Spin-orbit coupling from a two-component self-consistent approach. II. Non-collinear density functional theories
Authors: Desmarais Jacques K. , Flament Jean-Pierre , Erba Alessandro 
Published: August 2019

We revise formal and numerical aspects of collinear and noncollinear density functional theory (DFT) in the context of a two-component self-consistent treatment of spin-orbit coupling (SOC). While the extension of the standard one-component theory to a noncollinear magnetization is formally well-defined within the local density approximation, and therefore results in a numerically stable theory, this is not the case within the generalized gradient approximation (GGA). Previously reported formulations of noncollinear DFT based on GGA exchange-correlation potentials have several limitations: (i) they fail at reducing (either formally or numerically) to the proper collinear limit (i.e., when the magnetization is parallel or antiparallel to the z axis everywhere in space); (ii) they fail at ensuring a quantitative rotational invariance of the total energy and even a qualitative rotational invariance of the spatial distribution of the magnetization when a SOC operator is included in the Hamiltonian; (iii) they are numerically very unstable in regions of small magnetization. All of the above-mentioned problems are here shown (both formally and through test examples) to be solved by using instead a new formulation of noncollinear DFT for GGA functionals, which we call the “signed canonical” theory, as combined with an effective screening algorithm for unstable terms of the exchange-correlation potential in regions of small magnetization. All methods are implemented in the CRYSTAL program and tests are performed on simple molecules to compare the different formulations of noncollinear DFT.
All three authors of the article agree to the retraction of the article effective April 16, 2021.
Interlayer exchange coupling in (Ga,Mn)As ferromagnetic semiconductor multilayer systems
Authors: Lee Sanghoon , Chung Sunjae , Lee Hakjoon , Liu Xinyu , Dobrowolska M. , Furdyna J. K. 
Published: August 2019

Abstract
This paper describes interlayer exchange coupling (IEC) phenomena in ferromagnetic multilayer structures, focusing on the unique IEC features observed in ferromagnetic semiconductor (Ga,Mn)As-based systems. The dependence of IEC on the structural parameters, such as non-magnetic spacer thickness, number of magnetic layers, and carrier density in the systems has been investigated by using magnetotransport measurements. The samples in the series show both a typical anisotropic magnetoresistance (AMR) and giant magnetoresistance (GMR)-like effects indicating realization of both ferromagnetic (FM) and antiferromagnetic (AFM) IEC in (Ga,Mn)As-based multilayer structures. The results revealed that the presence of carriers in the non-magnetic spacer is an important factor to realize AFM IEC in this system. The studies further reveal that the IEC occurs over a much longer distance than predicted by current theories, strongly suggesting that the IEC in (Ga,Mn)As-based multilayers is a long-range interaction. Due to the long-range nature of IEC in the (Ga,Mn)As-based systems, the next nearest neighbor (NNN) IEC cannot be ignored and results in multi-step transitions during magnetization reversal that correspond to diverse spin configurations in the system. The strength of NNN IEC was experimentally determined by measuring minor loops that correspond to magnetization flips in specific (Ga,Mn)As layer in the multilayer system.
Progress on microscopic properties of diluted magnetic semiconductors by NMR and μSR
Authors: Gu Yilun , Guo Shengli , Ning Fanlong 
Published: August 2019

Abstract
Diluted magnetic semiconductors (DMSs) that possess both properties of semiconductors and ferromagnetism, have attracted a lot of attentions due to its potential applications for spin-sensitive electronic devices. Recently, a series of bulk form DMSs isostructural to iron-based superconductors have been reported, which can be readily investigated by microscopic experimental techniques such as nuclear magnetic resonance (NMR) and muon spin rotation (μSR). The measurements have demonstrated that homogeneous ferromagnetism is achieved in these DMSs. In this review article, we summarize experimental evidences from both NMR and μSR measurements. NMR results have shown that carriers facilitate the interactions between distant Mn atoms, while μSR results indicate that these bulk form DMSs and (Ga,Mn)As share a common mechanism for the ferromagnetic exchange interactions.
Two-dimensional ferromagnetic materials and related van der Waals heterostructures: a first-principle study
Authors: Zhai Baoxing , Du Juan , Li Xueping , Xia Congxin , Wei Zhongming 
Published: August 2019

Abstract
Since the successful fabrication of two-dimensional (2D) ferromagnetic (FM) monolayer CrI3 and Cr2Ge2Te6, 2D FM materials are becoming an exciting research topic in condensed matter physics and materials fields, as they provide a good platform to explore the fundamental physical properties of magnetic materials under 2D limit. In this review, we summarize the theoretical research progress of intrinsic 2D FM materials and related van der Waals heterostructures (vdWHs) including their electronic structures, magnetism, Curie temperature, valley polarization, and band alignment. Moreover, we also summarize recent researches on the methods that used to regulate the above properties of 2D FM materials and vdWHs, such as defects, doping, strain, electric field and interlayer coupling. These studies show that 2D FM materials have broad application prospects in spintronics and valleytronics. However, there are still many problems waiting to be solved on the way to practical application.
Decoding task engagement from distributed network electrophysiology in humans
Authors: Provenza Nicole R , Paulk Angelique C , Peled Noam , Restrepo Maria I , Cash Sydney S , Dougherty Darin D , Eskandar Emad N , Borton David A , Widge Alik S 
Published: August 2019

Abstract

Objective. Here, our objective was to develop a binary decoder to detect task engagement in humans during two distinct, conflict-based behavioral tasks. Effortful, goal-directed decision-making requires the coordinated action of multiple cognitive processes, including attention, working memory and action selection. That type of mental effort is often dysfunctional in mental disorders, e.g. when a patient attempts to overcome a depression or anxiety-driven habit but feels unable. If the onset of engagement in this type of focused mental activity could be reliably detected, decisional function might be augmented, e.g. through neurostimulation. However, there are no known algorithms for detecting task engagement with rapid time resolution. Approach. We defined a new network measure, fixed canonical correlation (FCCA), specifically suited for neural decoding applications. We extracted FCCA features from local field potential recordings in human volunteers to give a temporally continuous estimate of mental effort, defined by engagement in experimental conflict tasks. Main results. Using a small number of features per participant, we accurately decoded and distinguished task engagement from other mental activities. Further, the decoder distinguished between engagement in two different conflict-based tasks within seconds of their onset. Significance. These results demonstrate that network-level brain activity can detect specific types of mental efforts. This could form the basis of a responsive intervention strategy for decision-making deficits.
Photocatalytic degradation of methylene blue by TiO2/WO3-deoiled spent bleaching earth
Authors: Hindryawati N , Panggabean A S , N Subagyono RR D J , Sitinjak J Y 
Published: August 2019

Abstract
Degradation of methylene blue using pillared TiO2-WO3 onto deoiled spent bleaching earth (DSBE) has been conducted. Pillarization with TiO2-WO3 on DSBE using rarasaponin as surfactant. The structural and morphological of material has been carried out by X-ray fluorescence (XRF), and scanning electron microscopy coupled to the energy dispersive spectroscopy (SEM-EDX). Characterizations results show the increase composition of SiO2. The calcination result at 500°C show the TiO2-WO3 was deposited on the DSBE surface and suspected there is existence of Ti and W metals on the DSBE layer. The catalytic performance of TiO2-WO3/DSBE for photodegradation of methylene blue under visible light was 99.85 % within 30 minutes.
Antimicrobial assay of papaya seed ethanol extract (Carica papaya Linn) and phytochemical analysis of its active compounds
Authors: Masfufatun  , Yani N P W , Putri N P Y K 
Published: August 2019

Abstract
Natural drugs usage as alternative treatment has been increased in decades. This is due to the ‘back to nature’ life style of people and the side effect of natural drugs are relatively low. The prices of these natural drugs are cheaper as well. Papaya seed is one of the natural product with antimicrobial effect. The objectives of this research were to determine Minimum Inhibitory Concentration (MIC) of papaya seed ethanol extract to inhibit the growth of Candida albicans and Vibrio cholera and to analyze its active compounds. This research was performed using experimental design laboratory. The ethanol extract of papaya seed was obtained by maceration. The antimicrobial assay of papaya seed ethanol extract was performed using agar plate diffusion. The MIC determination of papaya seed ethanol extract was performed by 20, 15, 10, 5 and 1% concentration. The MIC of papaya seed ethanol extract against Candida albicans and Vibrio cholerae were in 5% concentration (diameter of inhibition zone=0.75 mm) and 15% (diameter of inhibition zone = 14.75 mm), respectively. The phytochemical assay of papaya seed ethanol extract showed there were alkaloids, flavonoids, steroids, polyphenols, tannins and saponins. It means that papaya seed ethanol extract has a good potential as antimicrobial therapy agent.
Metabolites fingerprint leaf extract of Bekkai plant, Albertisia papuana Becc as natural food seasonings using by Dayak Ethnics Community In North Kalimantan, Indonesia
Authors: Sudrajat S , Kartika R , Sudiastuti S 
Published: August 2019

Abstract
Bekkai plant, Albertisia papuana is one of the unique and valuable germplasm because it is utilized by Dayak Ethnics North Kalimantan community as natural flavoring food and medical treatment. There is little data about their phytocompounds characteristic. The objective of this research was to describe the metabolites fingerprint leaf extract of A.papuana which be consumed as natural food seasonings. Ethanol leaf extracts from Dayak community originated from Tanjung Selor, North Kalimantan were analyzed using untargeted Gas Chromatography-Mass Spectrometry (GCMS). The investigation led to the identification of 22 constituents, was dominated by Capsaicin (10.06%),Capsaicin(6.41%),Capsaicin (21.33%), Dihydrocapsaicin (2.16%) and Squalene 7.69%,2,5-Furandione,3-(dodecenyl)dihydro (5.88%), 2-Octadecyl-propane-1,3-dio l(5.55%), Phytol(5.14%), Citronellylformate(3.85%), A cembratrienol (3.93%), P=Ethyguaicol(3.39%), 4,22-Stigmastadiene -3-one (3.00%), Alpha limone diepoxide (2.79%), 2,6,6-Trimethylbicylo(3.1.1) heptane(1.00%), Pentadecyl bromide (2.28%), Hexadecanoic acid (2.21%),Z-10-Tetradecen-1-olacetate(2.03%),Heptamethylene dibromide(2.00%),7-Oxabicyclo[4.1.0]heptane,2,26-trimethyl-1-(3-methyl-1,3butadienyl)-5-m ethyllene(1.78%),4,4-Dimethyl-oct-5-enal(1.64%),4,4-Dimethylcholestan-3-one(1.86%),17-Pentatriacontene (1.12%).
Mathematics analysis of the effect of public health educational campaigns, screening and therapy on HIV/AIDS transmission
Authors: Marsudi  , Trisilowati  , Suryanto A , Darti I 
Published: August 2019

Abstract
In this paper, a deterministic mathematical models are formulated and analyzed to assess the effect of the public health educational campaigns, screening, and therapy on the dynamics of HIV/AIDS. The information causes a change in behavior resulting in three susceptible classes. We calculate the effective reproduction number using the next-generation matrix method. It has been shown that the disease-free equilibrium point is locally asymptotically stable when the effective reproduction number is less than unity. Sensitivity analysis of effective reproduction number with respect to the model parameters were carried out. The most sensitive parameter on the effective reproduction number is the contact rate of susceptible to unaware HIV infective followed by the screening rate and the least sensitive parameter is the progression rate of screened infective to full-blown AIDS. Numerical simulations and sensitivity analysis are carried out to support the analytical results and to determine the parameters influencing the dynamics of the disease.
K-means algorithm with improved initialization for clustering fruit plants
Authors: Amijaya F D T , Purnamasari I , Wasono  
Published: August 2019

Abstract
Clustering is one of data mining technique that can make a set of objects in such way that objects in the same group are more similar in some particular manner to each other than to those in other groups. K-means algorithm is one of clustering methods. Standard K- means algorithm has fast and simple computation, but it has the pitfall of randomly choosing initial the center of cluster. In this paper, we propose a mean method combined with interval index based on number cluster to choose initial the center of cluster. It can eliminate the randomness of the selection of initial the center of cluster, so it can find the optimum the center of cluster faster. The effectiveness of algorithm can be seen by maximum iteration of each algorithm. And fruit plants data will be used as data test.
Association rules with apriori algorithm and hash-based algorithm
Authors: Yulanda R D , Wahyuningsih S , Amijaya F D T 
Published: August 2019

Abstract
The purpose of this research is to determine the pattern of hijacking cases in Samarinda by using association rules and comparing apriori and hash-based. The data used for this research are secondary data from POLRESTA Samarinda which is processed using association rules algorithm with apriori and hash-based with minimum support of 10% and minimum confidence of 70%. The result of this research, in apriori, the pattern is often formed as many as 4 5-itemset combination while the hash-based obtained pattern that often formed by 3 3-itemset combination. In 2-itemset that is if the victim is female and young, then have a possibility of 46.67% chance of experiencing minor injuries with confidence of 90.9%, in 3-itemset if the victim is in location 1 and young, then have a possibility 53.33% chance of experiencing minor injuries with confidence of 88.89%, in 4-itemset if the victim in location 2, female and young then have a possibility 40% chance of experiencing minor injuries with confidence of 100%, in 5-itemset if the victim in location two, quite, female and young then have a possibility 26.67% chance of experiencing minor injuries with confidence of 100%.
Classification of nutritional status of toddlers using fuzzy k-nearest neighbor in every class (FK-NNC)
Authors: Izzah R U , Wahyuningsih S , Amijaya F D T 
Published: August 2019

Abstract
The purpose of this research is classify nutritional status of toddlers with algorithm fuzzy k-nearest in every class (FK-NNC). The FK-NNC algorithm is a modification concept of the nearest K neighbor for each class. The largest of the class on membership value will be selected as prediction classes. The optimal K value in FK-NNC algorithm uses k-fold cross validation. The optimal K values are searched by experimenting 1-fold cross validation, 4-fold cross validation and 10-fold cross validation. Accuracy rate of classify nutritional status of toddlers at the Wonorejo Health Center using the FK-NNC algorithm with an optimal K value. The results of this research obtained the optimal K value used in the FK-NNC algorithm at the Wonorejo Health Center is K=8 with 1-fold cross validation experiment. The value of K=8 was applied to the FK-NNC algorithm with a 1-fold cross validation experiment to predict class of nutritional status of toddlers in the Wonorejo Health Center. The percentage of accuracy produced as much as 100% with data proportion 90:10.
A teaching unit on electric vehicles to foster students’ decision-making competencies
Authors: Spatz V , Slezak C , Tampe J 
Published: August 2019

Abstract
According to the national education standards set by the standing Conference of Education Ministers in Germany in 2004, one of the central aims of science education in schools is to develop the competency of responsible decision-making. However, appropriate didactic and methodical concepts remain rare. Against this background, a targeted teaching unit for secondary schools including all teaching resources (worksheets, sample solutions, handouts, etc.) has been developed and evaluated. We have chosen electric vehicles as a contemporary context, since there seems to be no consensus in the public debate on this topic yet. Therefore, good arguments abound and can easily be found either for or against the new technology. As an introduction to the unit, students are asked to make a choice for one of two controversial, opposing articles presented to them. They are also asked to estimate how confident they are about their choice on a Likert scale. During the following lessons, students explore the topic not only through physical and technical principles, but also consider aspects outside the technical sphere. At the end students are asked to write their own composition in form of a newspaper article on the subject. The way they base their decisions on their arguments is analysed and assessed. This paper reports on the structure and the materials of the teaching unit as well as classroom experiences.
Active learning of buoyancy: an effective way to change students’ alternative conceptions about floating and sinking
Authors: Radovanović J , Sliško J , Stepanović Ilić I 
Published: August 2019

Abstract
We present research into the effects of traditional teaching and an applied active learning model to overcome students’ alternative conceptions on floating and sinking with a sample of 153 thirteen-year-old students in Serbia. An overview of the most important properties of the experimental model of active learning based on the IBSE approach is given. The results show significant differences in achievements between the control and the experimental group: the average normalized gain was 0.84±0.21 for experimental group and 0.04±0.25 for the control group, which points to the need for adoption of modern constructivist view on learning within the teaching process.
Active learning of phase and group velocities
Authors: Faletic S 
Published: August 2019

Abstract
I report on my observations during an active-learning activity on the topic of phase and group velocities with in-service physics teachers and a small group of high school students. The activity was designed to be as active as possible, and to guide the participants to the discovery (or reminder) that phase velocity is not the only velocity relevant to wave propagation. I observed that both groups, even after having been exposed to waves with dispersion, had difficulties using any velocity but phase velocity in their predictions and their reasoning. In the article, I describe the activity, and the observations. I discuss the possible reasons for the participants’ difficulties and suggest approaches that might improve the active-learning outcome.