bluuebunny/crossref_metadata_2025 huggingface dataset:
Ground moving target‐detection and focusing imaging under strong noise background
Authors: Zhou Yang , Bi Daping , Wang Xiaoping , Wang Shuliang , Shen Aiguo
Published: August 2019

This study proposes a detection algorithm for a three‐channel SAR system with weak ground moving target (GMT)‐detection and focusing imaging under strong noise background. First, the authors use DPCA cancellation technology to eliminate ground clutter signals. By accumulating the DPCA signal amplitude in the azimuth direction and setting a suitable threshold, they realise GMT detection under strong noise background. After extracting the target range cell DPCA signal, they use the interference processing method to estimate the real‐azimuth position of GMT. Then, they perform fractional Fourier transform processing on the extracted DPCA signal. Through the two‐dimensional search of the peak point on the plane of the parameter, the Doppler parameters and velocity estimation of the GMT are obtained. Finally, the azimuth‐matching filter is modified to achieve focusing imaging. Simulation results show that the detection probability of GMT is >95% when . When , the authors can achieve fairly accurate parameter estimation of GMT and ideal focusing imaging.
Sparse aperture wide‐angle inverse synthetic aperture radar imaging based on compressive sensing
Authors: Yingni Hou , Xia Wang
Published: August 2019

In high‐resolution inverse synthetic aperture radar (ISAR) imaging, if the authors enlarge observation angle, range migration would appear and that can cause defocus problem. For full aperture data, the authors can use keystone transform to mitigate the range migration. However the keystone transform is difficult to directly applied in azimuth sparse sampled data. In this article, for azimuth sparse sampled data, the authors analyse the echo model and devise an algorithm based on compressive sensing theory to reconstruct scatters in high‐resolution ISAR image. Simulation results demonstrate the validity of the method proposed in the article.
3D image reconstruction of spinning cone‐shaped target
Authors: Liu Xiaowen , Li Yan , Liu Jing , Zhang Qun , Luo Ying
Published: August 2019

By taking full advantage of the similarity of the two‐dimensional (2D) imaging result with the target's mapping on the 2D imaging plane, this paper proposes a 3D image reconstruction method for spinning cone‐shaped targets, which obtains the true 3D scattering centre distribution without image scaling and scattering centre trajectory. First, the mapping formulas for projecting the spatial point onto the imaging plane are derived. Then the 3D image reconstruction method is presented. With the proposed method, the 3D image reconstruction of spinning cone‐shaped target can be implemented effectively. Numeric simulations have proved the validity of the proposed method.
Improved multi‐target tracking algorithm based on SMC‐CBMeMBer for the airborne Doppler radar
Authors: Luo Muyang , Sun Hemin , Wu Weihua , Xie Xin , Jiang Surong
Published: August 2019

To effectively suppress clutter in airborne Doppler radar and improve multi‐target tracking (MTT) performance, this study proposes an improved MTT algorithm based on Sequential Monte Carlo Cardinality Balanced Multi‐target Multi‐Bernoulli (SMC‐CBMeMBer) filter. Firstly, the filter introduces Doppler information in the measurement process. Then, the more accurate likelihood function and state estimation are deduced again in the filtering update stage. Finally, the influence of particles number on the algorithm is analysed. Through the simulation experiment, when the number of particles is selected properly, the algorithm can more effectively suppress the clutter and improve the target tracking performance.
Full polarisation ISAR imaging based on joint sparse Bayesian compressive sensing
Authors: Gu Yalong , Pei Chunying , Wang Xin , Chen Rushan , Tao Shifei
Published: August 2019

This study proposes a joint sparse algorithm based on Bayesian compressive sensing to improve full polarisation inverse synthetic aperture radar (ISAR) imaging performance. The proposed method not only uses the sparseness of each single channel polarisation, but also takes into account the correlation of amplitude information between single‐polarised channels. Through the comprehensive use of single channel polarisation imaging results, a better full‐polarisation imaging result is achieved. Simulation results are used to verify the effectiveness of the method.
New imaging method for airborne circular trace stripmap SAR
Authors: Hui Yu , Wenying Wang , Wanming Lei , Pin Li
Published: August 2019

Circular trace stripmap synthetic aperture radar (SAR) (CTS‐SAR) is a new operation mode presented recently. Compared with linear trace stripmap SAR and staring SAR, it is similar to them. Meanwhile, it shows some unique features. The geometry relationship and work principle of CTS‐SAR are introduced and deduced. After analysing the moving characteristics of airborne platform, a novel imaging method with motion compensation for airborne CTS‐SAR is proposed. The impact of motion error and the performance of this new method are analysed. Finally, the results of computer simulation and real data processing validate the analysed results and the proposed imaging method.
Fast ISAR autofocus algorithm via sub‐aperture
Authors: Cai Jinjian , Song Yuanyuan , Sun Yinghao , Liu Feifeng
Published: August 2019

Translational motion compensation (TMC) is a significant step for inverse synthetic aperture radar (ISAR), while phase autofocus plays an important role in TMC. By eigenvalue decomposition (EVD), principle eigenvectors of the covariance matrix constructed by the complex range‐aligned signal can be acquired for ISAR‐phase autofocus. Nevertheless, for purpose of enhancing the cross‐range resolution, the observation pulse number should be increased. Large observation pulse number will lead to the heavy computational complexity due to EVD, which may overburden the system. To overcome this issue, a novel sub‐aperture EVD‐based method is proposed here. The full‐aperture signal is divided into multiple partially overlapped sub‐apertures with a novel partition criterion based on the average range profiles, then the conventional EVD‐based methods are utilised to obtain the phase errors in sub‐apertures. After the jump‐phase compensation, combine the phase‐error estimation of all sub‐aperture to complete the full‐aperture phase autofocus. With this method, the computational efficiency can be improved remarkably in typical scenarios, compared with the traditional autofocus algorithms based on EVD. Finally, results for the simulated data and the real measured data are demonstrated to verify the validity of the proposed algorithm.
Kernel-phase detection limits
Authors: Ceau A. , Mary D. , Greenbaum A. , Martinache F. , Sivaramakrishnan A. , Laugier R. , N’Diaye M.
Published: August 2019

Context. The James Webb Space Telescope (JWST) will offer high angular resolution observing capability in the near-infrared with masking interferometry on the Near-Infrared Imager and Slitless Spectrograph (NIRISS), and coronagraphic imaging on the Near-Infrared Camera (NIRCam) and the Mid-Infrared Instrument (MIRI). Full-aperture kernel-phase-based interferometry complements these observing modes by allowing us to probe for companions at small angular resolution while preserving the telescope throughput.

Aims. Our goal is to derive both theoretical and operational contrast-detection limits for the kernel-phase analysis of JWST NIRISS full-pupil observations using tools from hypothesis testing theory. The study is immediately applied to observations of faint brown dwarfs with this instrument, but the tools and methods introduced here are applicable in a wide variety of contexts.

Methods. We construct a statistically independent set of observable quantities from a collection of aberration-robust kernel phases. Three detection tests based on these observable quantities are designed and analysed, all having the property of guaranteeing a constant false-alarm rate for phase aberrations smaller than about one radian. One of these tests, the likelihood ratio or Neyman-Pearson test, provides a theoretical performance bound for any detection test.

Results. The operational detection method considered here is shown to exhibit only marginal power loss with respect to the theoretical bound. In principle, for the test set to a false-alarm probability of 1%, companions at contrasts reaching 103 and separations of 200 mas around objects of magnitude 14.1 are detectable with a probability of 68%. For the brightest objects observable using the full pupil of JWST and NIRISS, contrasts of up to 104 at separations of 200 mas could ultimately be achieved, barring significant wavefront drift. We also provide a statistical analysis of the uncertainties affecting the contrasts and separations that are estimated for the detected companions.

Conclusions. The proposed detection method is close to the ultimate bound and offers guarantees on the probability of making a false detection for binaries, as well as on the error bars for the estimated parameters of the binaries that will be detected by JWST NIRISS. This method is not only applicable to JWST NIRISS but to any imaging system with adequate sampling.
Update Allergologie im Kindesalter
Authors: Wagner Nicola , Sticherling Michael
Published: August 2019

Allergologische Erkrankungen im Kindesalter manifestieren sich mit diversen Symptomen. Das zunehmend breitere Spektrum verfügbarer spezifischer IgE auf rekombinante Allergene verbessert die Diagnostik und die Beurteilung ätiologischer Zusammenhänge einer allergologischen Symptomatik. Nahrungsmittelassoziierte Allergien und Intoleranzen nehmen zu und erfordern, insbesondere im Kindesalter, eine rasche Aufklärung des auslösenden Allergens. Die Empfehlungen zur allergologischen Diagnostik bei Arzneimittelallergie-/unverträglichkeit stehen als deutsche SK2-Leitlinie zur Verfügung. Ekzematöse Hautveränderungen können neben Atopie-assoziierten Ekzemreaktionen auch auf Kontaktallergien zurückzuführen sein, weshalb auch neue Kontaktallergene, wie Isobornylacrylat, in kontinuierlich messenden Glukosesensoren, differenzialdiagnostisch bedacht werden sollten.
Comparison of a Combined Strength and Handball-Specific Training vs. Isolated Strength Training in Handball Players Studying Physical Education
Authors: Hermassi Souhail , Haddad Monoem , Bouhafs El Ghali , Laudner Kevin G. , Schwesig René
Published: August 2019

Objectives The purpose of this study was to compare the effect of combined resistance training including handball-specific drill (CRT) with resistance training excluding handball-specific drill training (NSDT).

Materials and methods Twenty-two male handball players who studied physical education were randomly assigned to two groups: CRT (combined resistance training with sport-specific drill; n = 12) and NSDT (resistance training without any sport-specific drill training; n = 10). Over a 10-week period during the competitive season, the players performed a specific training program twice per week, which replaced their normal team handball training. The CRT regimen consisted of a combined (associated) resistance training and handball-specific drill, whereas the NSDT program consisted of a resistance training without handball-specific drill (dissociated). Pre- and post-test measures included squat jump and countermovement jumps, bench press, back half squats, throwing velocity during a 3-step jump throw, and a jump shot, repeated-sprint ability (six 2 × 15-m shuttle sprints) (RSA), medicine ball throw and anthropometric measurements.

Results In both groups, significant intervention effects (d ≥ 1.0) were seen for all sprint (3/3), throwing (3/3) and jump (2/2) measures. Regarding maximal strength parameters, an effect size lower than 0.5 was only detected in the NSDT group for half back squats (d = 0.48). The largest effects were observed in the NSDT group for squat jump (d = 6.20) and medicine ball throw (d = 6.07). Interaction effects (group × time) were found for 50 % (5/10) of parameters. The greatest difference between groups regarding performance development over time was detected for jump shot (interaction effect: η² = 0.748). In contrast, there was no difference in performance development in both groups over time for RSAbest (interaction effect: η² = 0.025).

Conclusions The current findings suggest that during the competitive season, 10 weeks of CRT with only two training sessions per week improved numerous measures of athletic performance in handball students of physical education. Such conditioning should be highly recommended as part of the annual training program of handball players.
AI in Health: State of the Art, Challenges, and Future Directions
Authors: Wang Fei , Preininger Anita
Published: August 2019

Introduction: Artificial intelligence (AI) technologies continue to attract interest from a broad range of disciplines in recent years, including health. The increase in computer hardware and software applications in medicine, as well as digitization of health-related data together fuel progress in the development and use of AI in medicine. This progress provides new opportunities and challenges, as well as directions for the future of AI in health.

Objective: The goals of this survey are to review the current state of AI in health, along with opportunities, challenges, and practical implications. This review highlights recent developments over the past five years and directions for the future.

Methods: Publications over the past five years reporting the use of AI in health in clinical and biomedical informatics journals, as well as computer science conferences, were selected according to Google Scholar citations. Publications were then categorized into five different classes, according to the type of data analyzed. Results: The major data types identified were multi-omics, clinical, behavioral, environmental and pharmaceutical research and development (R&D) data. The current state of AI related to each data type is described, followed by associated challenges and practical implications that have emerged over the last several years. Opportunities and future directions based on these advances are discussed.

Conclusion: Technologies have enabled the development of AI-assisted approaches to healthcare. However, there remain challenges. Work is currently underway to address multi-modal data integration, balancing quantitative algorithm performance and qualitative model interpretability, protection of model security, federated learning, and model bias.
Public Health and Epidemiology Informatics: Can Artificial Intelligence Help Future Global Challenges? An Overview of Antimicrobial Resistance and Impact of Climate Change in Disease Epidemiology
Authors: Rodríguez-González Alejandro , Zanin Massimiliano , Menasalvas-Ruiz Ernestina
Published: August 2019

Objectives: To provide an oveiview of the current application of artificial intelligence (AI) in the field of public health and epidemiology, with a special focus on antimicrobial resistance and the impact of climate change in disease epidemiology. Both topics are of vital importance and were included in the “Ten threats to global health in 2019“ report published by the World Health Organization.

Methods: We analysed publications that appeared in the last two years, between January 2017 and October 2018. Papers were searched using Google Scholar with the following keywords: public health, epidemiology, machine learning, data analytics, artificial intelligence, disease surveillance, climate change, antimicrobial resistance, and combinations thereof. Selected articles were organised by theme.

Results: In spite of a large interest in AI generated both within and outside the scientific community, and of the many opinions pointing towards the importance of a better use of data in public health, few papers have been published on the selected topics in the last two years. We identify several potential reasons, including the complexity of the integration of heterogeneous data, and the lack of sound and unbiased validation procedures.

Conclusions: As there is a better comprehension of AI and more funding available, artificial intelligence will become not only the centre of attention in informatics, but more importantly the source of innovative solutions for public health.
Health Information Management: Implications of Artificial Intelligence on Healthcare Data and Information Management
Authors: Stanfill Mary H. , Marc David T.
Published: August 2019

Objective: This paper explores the implications of artificial intelligence (AI) on the management of healthcare data and information and how AI technologies will affect the responsibilities and work of health information management (HIM) professionals. Methods: A literature review was conducted of both peer-reviewed literature and published opinions on current and future use of AI technology to collect, store, and use healthcare data. The authors also sought insights from key HIM leaders via semi-structured interviews conducted both on the phone and by email.

Results: The following HIM practices are impacted by AI technologies: 1) Automated medical coding and capturing AI-based information; 2) Healthcare data management and data governance; 3) Fbtient privacy and confidentiality; and 4) HIM workforce training and education.

Discussion: HIM professionals must focus on improving the quality of coded data that is being used to develop AI applications. HIM professional’s ability to identify data patterns will be an important skill as automation advances, though additional skills in data analysis tools and techniques are needed. In addition, HIM professionals should consider how current patient privacy practices apply to AI application, development, and use.

Conclusions: AI technology will continue to evolve as will the role of HIM professionals who are in a unique position to take on emerging roles with their depth of knowledge on the sources and origins of healthcare data. The challenge for HIM professionals is to identify leading practices for the management of healthcare data and information in an AI-enabled world.
A Broader Look: Camera-Based Vital Sign Estimation across the Spectrum
Authors: Antink Christoph Hoog , Lyra Simon , Paul Michael , Yu Xinchi , Leonhardt Steffen
Published: August 2019

Objectives: Camera-based vital sign estimation allows the contactless assessment of important physiological parameters. Seminal contributions were made in the 1930s, 1980s, and 2000s, and the speed of development seems ever increasing. In this suivey, we aim to overview the most recent works in this area, describe their common features as well as shortcomings, and highlight interesting “outliers”.

Methods: We performed a comprehensive literature research and quantitative analysis of papers published between 2016 and 2018. Quantitative information about the number of subjects, studies with healthy volunteers vs. pathological conditions, public datasets, laboratory vs. real-world works, types of camera, usage of machine learning, and spectral properties of data was extracted. Moreover, a qualitative analysis of illumination used and recent advantages in terms of algorithmic developments was also performed.

Results: Since 2016, 116 papers were published on camera-based vital sign estimation and 59% of papers presented results on 20 or fewer subjects. While the average number of participants increased from 15.7 in 2016 to 22.9 in 2018, the vast majority of papers (n=100) were on healthy subjects. Four public datasets were used in 10 publications. We found 27 papers whose application scenario could be considered a real-world use case, such as monitoring during exercise or driving. These include 16 papers that dealt with non-healthy subjects. The majority of papers (n=61) presented results based on visual, red-green-blue (RGB) information, followed by RGB combined with other parts of the electromagnetic spectrum (n=18), and thermography only (n=12), while other works (n=25) used other mono- or polychromatic non-RGB data. Surprisingly, a minority of publications (n=39) made use of consumer-grade equipment. Lighting conditions were primarily uncontrolled or ambient. While some works focused on specialized aspects such as the removal of vital sign information from video streams to protect privacy or the influence of video compression, most algorithmic developments were related to three areas: region of interest selection, tracking, or extraction of a one-dimensional signal. Seven papers used deep learning techniques, 17 papers used other machine learning approaches, and 92 made no explicit use of machine learning.

Conclusion: Although some general trends and frequent shortcomings are obvious, the spectrum of publications related to camera-based vital sign estimation is broad. While many creative solutions and unique approaches exist, the lack of standardization hinders comparability of these techniques and of their performance. We believe that sharing algorithms and/ or datasets will alleviate this and would allow the application of newer techniques such as deep learning.
Personalized Medicine Implementation with Non-traditional Data Sources: A Conceptual Framework and Survey of the Literature
Authors: Taylor Casey Overby , Tarczy-Hornoch Peter
Published: August 2019

Objectives: With the explosive growth in availability of health data captured using non-traditional sources, the goal for this work was to evaluate the current biomedical literature on theory- driven studies investigating approaches that leverage non- traditional data in personalized medicine applications.

Methods: We conducted a literature assessment guided by the personalized medicine unsolicited health information (pUHl) conceptual framework incorporating diffusion of innovations and task-technology fit theories.

Results: The assessment provided an oveiview of the current literature and highlighted areas for future research. In particular, there is a need for: more research on the relationship between attributes of innovation and of societal structure on adoption; new study designs to enable flexible communication channels; more work to create and study approaches in healthcare settings; and more theory-driven studies with data-driven interventions.

Conclusion: This work introduces to an informatics audience an elaboration on personalized medicine implementation with non-traditional data sources by blending it with the pUHl conceptual framework to help explain adoption. We highlight areas to pursue future theory-driven research on personalized medicine applications that leverage non-traditional data sources.
The French Health Data Hub and the German Medical Informatics Initiatives: Two National Projects to Promote Data Sharing in Healthcare
Authors: Cuggia Marc , Combes Stéphanie
Published: August 2019

Objective: The diversity and volume of health data have been rapidly increasing in recent years. While such big data hold significant promise for accelerating discovery, data use entails many challenges including the need for adequate computational infrastructure and secure processes for data sharing and access. In Europe, two nationwide projects have been launched recently to support these objectives. This paper compares the French Health Data Hub initiative (HDH) to the German Medical Informatics Initiatives (MII).

Method: We analysed the projects according to the following criteria: (i) Global approach and ambitions, (ii) Use cases, (iii) Governance and organization, (iv) Technical aspects and interoperability, and (v) Data privacy access/data governance.

Results: The French and German projects share the same objectives but are different in terms of methodologies. The HDH project is based on a top-down approach and focuses on a shared computational infrastructure, providing tools and services to speed projects between data producers and data users. The MII project is based on a bottom-up approach and relies on four consortia including academic hospitals, universities, and private partners.

Conclusion: Both projects could benefit from each other. A Franco-German cooperation, extended to other countries of the European Union with similar initiatives, should allow sharing and strengthening efforts in a strategic area where competition from other countries has increased.
Clinical Research Informatics: Contributions from 2018
Authors: Daniel Christel , Kalra Dipak ,   Section Editors for the IMIA Yearbook Section on Clinical Research Informatics
Published: August 2019

Objectives: To summarize key contributions to current research in the field of Clinical Research Informatics (CRI) and to select best papers published in 2018.

Method: A bibliographic search using a combination of MeSH descriptors and free-text terms on CRI was performed using PubMed, followed by a double-blind review in order to select a list of candidate best papers to be then peer-reviewed by external reviewers. After peer-review ranking, a consensus meeting of the editorial team was organized to conclude on the selection of best papers.

Results: Among the 1,469 retrieved papers published in 2018 in the various areas of CRI, the full review process selected four best papers. The first best paper describes a simple algorithm detecting co-morbidities in Electronic Healthcare Records (EHRs) using a clinical data warehouse and a knowledge base. The authors of the second best paper present a federated algorithm for predicting heart failure hospital admissions based on patients' medical history described in their distributed EHRs. The third best paper reports the evaluation of an open source, interoperable, and scalable data quality assessment tool measuring completeness of data items, which can be run on different architectures (EHRs and Clinical Data Warehouses (CDWs) based on PCORnet or OMOP data models). The fourth best paper reports a data quality program conducted across 37 hospitals addressing data quality Issues through the whole data life cycle from patient to researcher.

Conclusions: Research efforts in the CRI field currently focus on consolidating promises of early Distributed Research Networks aimed at maximizing the potential of large-scale, harmonized data from diverse, quickly developing digital sources. Data quality assessment methods and tools as well as privacy-enhancing techniques are major concerns. It is also notable that, following examples in the US and Asia, ambitious regional or national plans in Europe are launched that aim at developing big data and new artificial intelligence technologies to contribute to the understanding of health and diseases in whole populations and whole health systems, and returning actionable feedback loops to improve existing models of research and care. The use of “real-world" data is continuously increasing but the ultimate role of this data in clinical research remains to be determined.
Findings from the 2019 International Medical Informatics Association Yearbook Section on Health Information Management
Authors: Bloomrosen Meryl , Berner Eta S. ,   Section Editors for the IMIA Yearbook Section on Health Information Management
Published: August 2019

Objectives: To summarize the recent literature and research and present a selection of the best papers published in 2018 in the field of Health Information Management (HIM) and Health Informatics.

Methods: A systematic review of the literature was performed, with the help of a medical librarian, by the two editors of the HIM section of the International Medical Informatics Association (IMIA) Yearbook. In order to include papers that would address the special theme of the 2019 Yearbook on artificial intelligence (AI) as well as HIM, we searched bibliographic databases for HIM-related papers with an AI focus using both Medical Subject Headings (MeSH) descriptors and keywords in titles and abstracts. A shortlist of 15 candidate best papers was first selected by section editors before being peer-reviewed by independent external reviewers.

Results: While there were a significant number of manuscripts that addressed issues relevant to HIM, there were virtually none with MeSH headings indicating an HIM focus. Manuscripts that were considered related to the HIM field in terms of the practice of health information management as well as the profession included those that examined using machine learning and other AI approaches to identify protected health information in clinical text to aid with de-identification, automated coding approaches to translate free-text into standardized codes, and natural language processing approaches to extract clinical data to assist with populating cancer and other registries.

Conclusions: The papers discussed in the HIM section reflect the special theme of the use of AI in healthcare on issues particularly relevant to the field of HIM. This synopsis discusses these papers and recommends that HIM practitioners be more involved in research and that researchers in AI and related areas recognize the applicability and relevance of their work to the field of HIM.
Contributions from the 2018 Literature on Bioinformatics and Translational Informatics
Authors: Smaïl-Tabbone Malika , Rance Bastien ,   Section Editors for the IMIA Yearbook Section on Bioinformatics and Translational Informatics
Published: August 2019

Objectives: To summarize recent research and select the best papers published in 2018 in the field of Bioinformatics and Translational Informatics (BTI) for the corresponding section of the International Medical Informatics Association (IMIA) Yearbook.

Methods: A literature review was performed for retrieving from PubMed papers indexed with keywords and free terms related to BTI. Independent review allowed the two section editors to select a list of 14 candidate best papers which were subsequently peer-reviewed. A final consensus meeting gathering the whole IMIA Yearbook editorial committee was organized to finally decide on the selection of the best papers.

Results: Among the 636 retrieved papers published in 2018 in the various subareas of BTI, the review process selected four best papers. The first paper presents a computational method to identify molecular markers for targeted treatment of acute myeloid leukemia using multi-omics data (genome-wide gene expression profiles) and in vitro sensitivity to 160 chemotherapy drugs. The second paper describes a deep neural network approach to predict the survival of patients suffering from glioma on the basis of digitalised pathology images and genomics biomarkers. The authors of the third paper adopt a pan-cancer approach to take benefit of multi-omics data for drug repurposing. The fourth paper presents a graph-based semi-supervised method to accurate phenotype classification applied to ovarian cancer.

Conclusions: Thanks to the normalization of open data and open science practices, research in BTI continues to develop and mature. Noteworthy achievements are sophisticated applications of leading edge machine-learning methods dedicated to personalized medicine.
Artificial Intelligence in Health Informatics: Hype or Reality?
Authors: Hollis Kate Fultz , Soualmia Lina F. , Séroussi Brigitte
Published: August 2019

Objectives: To provide an introduction to the 2019 International Medical Informatics Association (IMIA) Yearbook by the editors.

Methods: This editorial presents an overview and introduction to the 2019 IMIA Yearbook which includes the special topic “Artificial Intelligence in Health: New Opportunities, Challenges, and Practical Implications". The special topic is discussed, the IMIA President’s statement is introduced, and changes in the Yearbook editorial team are described.

Results: Artificial intelligence (AI) in Medicine arose in the 1970’s from new approaches for representing expert knowledge with computers. Since then, AI in medicine has gradually evolved toward essentially data-driven approaches with great results in image analysis. However, data integration, storage, and management still present clear challenges among which the lack of explanability of the results produced by data-driven AI methods.

Conclusion: With more health data availability, and the recent developments of efficient and improved machine learning algorithms, there is a renewed interest for AI in medicine.

The objective is to help health professionals improve patient care while also reduce costs. However, the other costs of AI, including ethical issues when processing personal health data by algorithms, should be included.
Nonperturbative evaluation of the partition function for the real scalar quartic QFT on the Moyal plane at weak coupling
Authors: de Jong J. , Wulkenhaar R.
Published: August 2019

The remarkable properties of the real scalar quartic quantum field theory on the Moyal plane in combination with its similarities to the Kontsevich model make the model’s partition function an interesting object to study. However, the intertwinement of the eigenvalues of the external matrix prevents a direct evaluation. In this paper, we develop a factorization procedure to circumvent this problem and discuss it in the context of the real scalar quartic quantum field theory on the Moyal plane. The factorization consists of integration against the asymptotic volume of the diagonal subpolytope of symmetric stochastic matrices. The partition function in the weak coupling regime can be computed in this way. This method should also extend to other regimes.
Spectroscopic study of CO2 and CO2–N2 mixture plasma using dielectric barrier discharge
Authors: Khan M. I. , Rehman N. U. , Khan Shabraz , Ullah Naqib , Masood Asad , Ullah Aman
Published: August 2019

Nowadays, increasing concentration of CO2 in the atmosphere is a major threat for the environment and is a main reason for global warming. Variation in gas temperature and dissociation of CO2 into its by-products (CO and O) in a home-made dielectric barrier discharge (DBD) reactor have been reported as a function of discharge parameters, i.e., applied voltage and gas flow rate. To estimate the dissociation fraction of CO2 in the DBD reactor, the optical emission actinometry technique is employed in which 5% N2 is used as an actinometer. Emission lines of the Angstrom band of CO at 451.09 nm (B1∑  +v′=0−A1π, v″=0) and the 2nd positive system of N2 at 337.01 nm (C3πuv′=0−B3πg,v″=0) are used for actinometry measurements. To estimate the rate coefficients used in actinometry measurements, gas temperature is measured using the Boltzmann plot technique, from the rotational spectra of the Q-branch of the Angstrom band CO (0–1). To avoid discrepancy in gas temperature measurements, rotational temperature of the 2nd positive system, the N2 (0–1) band, is also measured. For this, synthetic spectra have been fitted over the experimentally recorded spectrum of the N2 (0–1) band. A slight difference in gas temperature has been noted for the Angstrom band of CO and the 2nd positive system of nitrogen. Conversely, an increasing trend in the dissociation fraction of CO2 with an increase in the applied voltage is noted. About 34% dissociation fraction is achieved for 10 kV applied voltage at a flow rate of 25 SCCM. With an increase in the gas flow rate (25–200 SCCM), a decrease in the dissociation fraction of CO2 from 34% to 11% is noted.
Ultra-wideband and wide-angle polarization rotator based on double W-shaped metasurface
Authors: Zhao Yinrui , Qi Buxiong , Niu Tiaoming , Mei Zhonglei , Qiao Liang , Zhao Yaodong
Published: August 2019

In this work, we design a novel polarization converter based on a metasurface with double w-shaped unit cells. The proposed polarization converter can convert linearly polarized incident waves into its cross polarized reflective counterparts in a very wide band with high efficiency. Theoretical analysis and simulation results show that the proposed polarization converter can achieve a 90° polarization rotation, while the polarization conversion ratio (PCR) is above 90% in the frequency range from 8.44 GHz to 24.96 GHz, and the relative bandwidth can be up to 99%. The measured results agree well with simulation results. The designed double w-shaped metasurface has a very simple geometry, and can realize a highly-efficient and broadband polarization rotation. Therefore, it has practical applications in wireless communication systems, imaging, radar stealth technology, and other fields.
Enhanced sampling in molecular dynamics
Authors: Yang Yi Isaac , Shao Qiang , Zhang Jun , Yang Lijiang , Gao Yi Qin
Published: August 2019

Although molecular dynamics simulations have become a useful tool in essentially all fields of chemistry, condensed matter physics, materials science, and biology, there is still a large gap between the time scale which can be reached in molecular dynamics simulations and that observed in experiments. To address the problem, many enhanced sampling methods were introduced, which effectively extend the time scale being approached in simulations. In this perspective, we review a variety of enhanced sampling methods. We first discuss collective-variables-based methods including metadynamics and variationally enhanced sampling. Then, collective variable free methods such as parallel tempering and integrated tempering methods are presented. At last, we conclude with a brief introduction of some newly developed combinatory methods. We summarize in this perspective not only the theoretical background and numerical implementation of these methods but also the new challenges and prospects in the field of the enhanced sampling.
Strain-engineering of charge transport in the correlated Dirac semimetal of perovskite CaIrO3 thin films
Authors: Masuko M. , Fujioka J. , Nakamura M. , Kawasaki M. , Tokura Y.
Published: August 2019

We have investigated the charge transport in thin films of correlated Dirac semimetal of perovskite CaIrO3 by measurements of resistivity and optical spectra. The semimetallic transport of either electron-type or hole-type carrier is observed in the strain-relaxed thin films. By controlling the strain relaxation via thermal annealing, the carrier density decreases in both n-type and p-type samples, while enhancing the carrier mobility up to 160 cm2 V−1 s−1 at an electron density of 2.5 × 1018 cm−3 at 2 K. We propose that the energy of Dirac line node, which locates in proximity to the Fermi level, varies with the lattice distortion or strain-sensitive defect character, causing the sign change in the charge carrier as well as the mobility enhancement.
Macromolecular architecture and complex viscosity
Authors: Kanso M. A. , Giacomin A. J. , Saengow C. , Piette J. H.
Published: August 2019

General rigid bead-rod theory [O. Hassager, “Kinetic theory and rheology of bead-rod models for macromolecular solutions. II. Linear unsteady flow properties,” J. Chem. Phys. 60(10), 4001–4008 (1974)] explains polymer viscoelasticity from macromolecular orientation. By means of general rigid bead-rod theory, we relate the complex viscosity of polymeric liquids to the architecture of axisymmetric macromolecules. In this work, we explore the zero-shear and complex viscosities of 24 different axisymmetric polymer configurations. When nondimensionalized with the zero-shear viscosity, the complex viscosity depends on the dimensionless frequency and the sole dimensionless architectural parameter, the macromolecular lopsidedness. In this work, in this way, we compare and contrast the elastic and viscous components of the complex viscosities of macromolecular chains that are straight, branched, ringed, or star-branched. We explore the effects of branch position along a straight chain, branched-chain backbone length, branched-chain branch-functionality, branch spacing along a straight chain (including pom-poms), the number of branches along a straight chain, ringed polymer perimeter, branch-functionality in planar stars, and branch dimensionality.
Neural networks-based variationally enhanced sampling
Authors: Bonati Luigi , Zhang Yue-Yu , Parrinello Michele
Published: August 2019

Significance

Atomistic-based simulations are one of the most widely used tools in contemporary science. However, in the presence of kinetic bottlenecks, their power is severely curtailed. In order to mitigate this problem, many enhanced sampling techniques have been proposed. Here, we show that by combining a variational approach with deep learning, much progress can be made in extending the scope of such simulations. Our development bridges the fields of enhanced sampling and machine learning and allows us to benefit from the rapidly growing advances in this area.
Coherent Coupling between Microwave and Optical Fields via Cold Atoms*
Authors: Liang Zhen-Tao , Lv Qing-Xian , Zhang Shan-Chao , Wu Wei-Tao , Du Yan-Xiong , Yan Hui , Zhu Shi-Liang
Published: August 2019

We demonstrate a long-coherent-time coupling between microwave and optical fields through cold atomic ensembles. The phase information of the microwave field is stored in a coherent superposition state of a cold atomic ensemble and is then read out by two optical fields after 12 ms. A similar operation of mapping the phase of optical fields into a cold atomic ensemble and then retrieving by microwave is also demonstrated. These studies demonstrate that long-coherent-time cold atomic ensembles could resonantly couple with microwave and optical fields simultaneously, which paves the way for realizing high-efficiency, high-bandwidth, and noiseless atomic quantum converters.
A Quasi-1D Potential for Bose Gas Phase Fluctuations*
Authors: Yang Shi-Feng , Xu Zi-Tong , Wang Kai , Li Xiu-Fei , Zhai Yue-Yang , Chen Xu-Zong
Published: August 2019

An elongated trap potential for cold atoms is designed based on a quadrupole-Ioffe configuration. Phase fluctuations in a Bose–Einstein condensate (BEC), which is confined by the trap, are studied. We simulate the atom density distribution induced by fluctuation after time of flight from this elongated trap potential and study the temperature measurement method related to the distribution. Furthermore, taking advantage of the tight confinement and radio frequency dressing technique, we propose a double well potential for splitting BECs. Our results are helpful for improving understanding of low-dimensional quantum gases and provide important guidance for atomic interferometry.
Critical One-Dimensional Absorption-Desorption with Long-Ranged Interaction*
Authors: Liu Xiaowei , Guo Jingyuan , Li Zhibing
Published: August 2019

An absorption-desorption model with long-ranged interaction is simulated by the dynamic Monte Carlo method. The dynamic process has an inert phase and an active phase that is controlled by the absorption rate. In the active phase, the number of vacancies increases with time exponentially, while in the inert phase the vacant sites will be occupied by adsorbates rapidly. At the critical absorption rate, both the number of vacancies and the time-depending active probability exhibit power-law behavior. We determine the critical absorption rate and the scaling exponents of the power-laws. The effect of the interaction range of desorption on the critical exponents is investigated. In the short-ranged interaction limit, the critical exponents of Schlögl’s first model are recovered. The model may describe the stability of the inner Helmholtz layer, an essential component of the electrochemical double-layer capacitor at a nanowire.
A Silicon Shallow-Ridge Waveguide Integrated Superconducting Nanowire Single Photon Detector Towards Quantum Photonic Circuits*
Authors: Yu Lingjie , Wang Heqing , Li Hao , Wang Zhen , Huang Yidong , You Lixing , Zhang Wei
Published: August 2019

A silicon shallow-ridge waveguide integrated superconducting nanowire single photon detector is designed and fabricated. At the bias current of 11.6 μA, 4% on-chip detection efficiency near 1550 nm wavelength is achieved with the dark count rate of 3 Hz and a timing jitter of 75 ps. This device shows the potential application in the integration of superconducting nanowire single photon detectors with a complex quantum photonic circuit.
The predicaments and expectations in development of magnetic semiconductors
Authors: Cao Qiang , Yan Shishen
Published: August 2019

Over the past half a century, considerable research activities have been directing towards the development of magnetic semiconductors that can work at room temperature. These efforts were aimed at seeking room temperature magnetic semiconductors with strong and controllable s, p–d exchange interaction. With this s, p–d exchange interaction, one can utilize the spin degree of freedom to design applicable spintronics devices with very attractive functions that are not available in conventional semiconductors. Here, we first review the progress in understanding of this particular material and the dilemma to prepare a room temperature magnetic semiconductor. Then we discuss recent experimental progresses to pursue strong s, p–d interaction to realize room temperature magnetic semiconductors, which are achieved by introducing a very high concentration of magnetic atoms by means of low-temperature nonequilibrium growth.
Mn-doped topological insulators: a review
Authors: Teng Jing , Liu Nan , Li Yongqing
Published: August 2019

Topological insulators (TIs) host robust edge or surface states protected by time-reversal symmetry (TRS), which makes them prime candidates for applications in spintronic devices. A promising avenue of research for the development of functional TI devices has involved doping of three-dimensional (3D) TI thin film and bulk materials with magnetic elements. This approach aims to break the TRS and open a surface band gap near the Dirac point. Utilizing this gapped surface state allows for a wide range of novel physical effects to be observed, paving a way for applications in spintronics and quantum computation. This review focuses on the research of 3D TIs doped with manganese (Mn). We summarize major progress in the study of Mn doped chalcogenide TIs, including Bi2Se3, Bi2Te3, and Bi2(Te,Se)3. The transport properties, in particular the anomalous Hall effect, of the Mn-doped Bi2Se3 are discussed in detail. Finally, we conclude with future prospects and challenges in further studies of Mn doped TIs.
Perspectives on exfoliated two-dimensional spintronics
Authors: Li Xiaoxi , Dong Baojuan , Sun Xingdan , Wang Hanwen , Yang Teng , Yu Guoqiang , Vitto Han Zheng
Published: August 2019

Magnetic orderings, i.e., the spontaneous alignment of electron spins below a critical temperature, have been playing key roles in modern science and technologies for both the wide applications of magnetic recording for information storage and the vibrant potential of solid state electronic spin devices (also known as spintronics) for logic operations. In the past decades, thanks to the development of thin film technologies, magnetic thin films via sputtering or epitaxial growth have made the spintronic devices possible at the industrial scale. Yet thinner materials at lower costs with more versatile functionalities are highly desirable for advancing future spintronics. Recently, van der Waals magnetic materials, a family of magnets that can in principle be exfoliated down to the monolayer limit, seem to have brought tremendous opportunities: new generation van der Waals spintronic devices can be seamlessly assembled with possible applications such as optoelectronics, flexible electronics, and etc. Moreover, those exfoliated spintronic devices can potentially be compatible with the famed metal-oxide field effect transistor architectures, allowing the harness of spin performances through the knob of an electrostatic field.