Showing papers by "Korea University published in 2017"
Theo Vos1, Amanuel Alemu Abajobir, Kalkidan Hassen Abate2, Cristiana Abbafati3 +775 more•Institutions (305)
TL;DR: The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of prevalence, incidence, and years lived with disability (YLDs) for 328 causes in 195 countries and territories from 1990 to 2016.
10,401 citations
TL;DR: The introduction of additional iodide ions into the organic cation solution, which is used to form the perovskite layers through an intramolecular exchanging process, decreases the concentration of deep-level defects, enabling the fabrication of PSCs with a certified power conversion efficiency.
Abstract: The formation of a dense and uniform thin layer on the substrates is crucial for the fabrication of high-performance perovskite solar cells (PSCs) containing formamidinium with multiple cations and mixed halide anions. The concentration of defect states, which reduce a cell’s performance by decreasing the open-circuit voltage and short-circuit current density, needs to be as low as possible. We show that the introduction of additional iodide ions into the organic cation solution, which are used to form the perovskite layers through an intramolecular exchanging process, decreases the concentration of deep-level defects. The defect-engineered thin perovskite layers enable the fabrication of PSCs with a certified power conversion efficiency of 22.1% in small cells and 19.7% in 1-square-centimeter cells.
4,603 citations
Ashkan Afshin, Mohammad H. Forouzanfar, Marissa B Reitsma, Patrick J Sur +164 more•Institutions (70)
TL;DR: The rapid increase in the prevalence and disease burden of elevated BMI highlights the need for continued focus on surveillance of BMI and identification, implementation, and evaluation of evidence‐based interventions to address this problem.
Abstract: BACKGROUND Although the rising pandemic of obesity has received major attention in many countries, the effects of this attention on trends and the disease burden of obesity remain uncertain. METHOD ...
4,519 citations
Simon I. Hay, Amanuel Alemu Abajobir1, Kalkidan Hassen Abate2, Cristiana Abbafati3 +800 more•Institutions (32)
TL;DR: At a global level, DALYs and HALE continue to show improvements and the importance of continued health interventions, which has changed in most locations in pace with the gross domestic product per person, education, and family planning.
3,029 citations
TL;DR: This review covers computer-assisted analysis of images in the field of medical imaging and introduces the fundamentals of deep learning methods and their successes in image registration, detection of anatomical and cellular structures, tissue segmentation, computer-aided disease diagnosis and prognosis, and so on.
Abstract: This review covers computer-assisted analysis of images in the field of medical imaging. Recent advances in machine learning, especially with regard to deep learning, are helping to identify, classify, and quantify patterns in medical images. At the core of these advances is the ability to exploit hierarchical feature representations learned solely from data, instead of features designed by hand according to domain-specific knowledge. Deep learning is rapidly becoming the state of the art, leading to enhanced performance in various medical applications. We introduce the fundamentals of deep learning methods and review their successes in image registration, detection of anatomical and cellular structures, tissue segmentation, computer-aided disease diagnosis and prognosis, and so on. We conclude by discussing research issues and suggesting future directions for further improvement.
2,653 citations
Gregory A. Roth1, Catherine O. Johnson1, Amanuel Alemu Abajobir2, Foad Abd-Allah3 +170 more•Institutions (99)
TL;DR: The GBD (Global Burden of Disease) 2015 study integrated data on disease incidence, prevalence, and mortality to produce consistent, up-to-date estimates for cardiovascular burden, finding that CVDs remain a major cause of health loss for all regions of the world.
2,525 citations
Posted Content•
TL;DR: A unified model architecture of StarGAN allows simultaneous training of multiple datasets with different domains within a single network, which leads to StarGAN's superior quality of translated images compared to existing models as well as the novel capability of flexibly translating an input image to any desired target domain.
Abstract: Recent studies have shown remarkable success in image-to-image translation for two domains. However, existing approaches have limited scalability and robustness in handling more than two domains, since different models should be built independently for every pair of image domains. To address this limitation, we propose StarGAN, a novel and scalable approach that can perform image-to-image translations for multiple domains using only a single model. Such a unified model architecture of StarGAN allows simultaneous training of multiple datasets with different domains within a single network. This leads to StarGAN's superior quality of translated images compared to existing models as well as the novel capability of flexibly translating an input image to any desired target domain. We empirically demonstrate the effectiveness of our approach on a facial attribute transfer and a facial expression synthesis tasks.
2,033 citations
Johns Hopkins University1, Leipzig University2, Korea University3, Yale University4, West Virginia University5, University of Barcelona6, St George's, University of London7, Indiana University8, National Yang-Ming University9, Cleveland Clinic10, Aarhus University11, University at Buffalo12, Imperial College London13, Primary Children's Hospital14, Erasmus University Rotterdam15, Yeshiva University16, Ghent University17, Baylor University18, Virginia Commonwealth University19, Harvard University20, Federal University of São Paulo21, University of California, San Francisco22, Beaumont Hospital23, Boston University24, University of Oklahoma25, Carlos III Health Institute26, University of Michigan27, University of Melbourne28, Saint Louis University29, Université de Montréal30, University of Pennsylvania31, McGill University32, Mayo Clinic33, Lahey Hospital & Medical Center34, Royal Adelaide Hospital35, University of Milan36, University of Toronto37, Loyola University Chicago38, Jikei University School of Medicine39
TL;DR: This 2017 Consensus Statement is to provide a state-of-the-art review of the field of catheter and surgical ablation of AF and to report the findings of a writing group, convened by these five international societies.
1,626 citations
University of Ulsan1, Osaka University2, Taipei Veterans General Hospital3, University Health System4, Chang Gung University5, Samsung Medical Center6, National Taiwan University7, Korea University8, China Medical University (Taiwan)9, Kindai University10, Seoul National University Bundang Hospital11, Keio University12, Kyungpook National University13, Japanese Foundation for Cancer Research14, Seoul National University Hospital15, Yonsei University16, National Cheng Kung University17, National Health Research Institutes18
TL;DR: In this phase 3 study, the survival benefits indicate that nivolumab might be a new treatment option for heavily pretreated patients with advanced gastric or gastro-oesophageal junction cancer.
1,512 citations
TL;DR: A novel methodology for interpreting generic multilayer neural networks by decomposing the network classification decision into contributions of its input elements by backpropagating the explanations from the output to the input layer is introduced.
1,247 citations
TL;DR: The aim of this review is to provide a comprehensive summary of the removal and fate of PPCPs in different treatment facilities as well as the optimum methods for their elimination in STP and WTP systems.
TL;DR: In this article, a deep tensor neural network is used to predict atomic energies and local chemical potentials in molecules, reliable isomer energies, and molecules with peculiar electronic structure.
Abstract: Learning from data has led to paradigm shifts in a multitude of disciplines, including web, text and image search, speech recognition, as well as bioinformatics. Can machine learning enable similar breakthroughs in understanding quantum many-body systems? Here we develop an efficient deep learning approach that enables spatially and chemically resolved insights into quantum-mechanical observables of molecular systems. We unify concepts from many-body Hamiltonians with purpose-designed deep tensor neural networks, which leads to size-extensive and uniformly accurate (1 kcal mol−1) predictions in compositional and configurational chemical space for molecules of intermediate size. As an example of chemical relevance, the model reveals a classification of aromatic rings with respect to their stability. Further applications of our model for predicting atomic energies and local chemical potentials in molecules, reliable isomer energies, and molecules with peculiar electronic structure demonstrate the potential of machine learning for revealing insights into complex quantum-chemical systems. Machine learning is an increasingly popular approach to analyse data and make predictions. Here the authors develop a ‘deep learning’ framework for quantitative predictions and qualitative understanding of quantum-mechanical observables of chemical systems, beyond properties trivially contained in the training data.
TL;DR: After standard neoadjuvant chemotherapy containing anthracycline, taxane, or both, the addition of adjuvant capecitabine therapy was safe and effective in prolonging disease‐free survival and overall survival among patients with HER2‐negative breast cancer who had residual invasive disease on pathological testing.
Abstract: BackgroundPatients who have residual invasive carcinoma after the receipt of neoadjuvant chemotherapy for human epidermal growth factor receptor 2 (HER2)–negative breast cancer have poor prognoses. The benefit of adjuvant chemotherapy in these patients remains unclear. MethodsWe randomly assigned 910 patients with HER2-negative residual invasive breast cancer after neoadjuvant chemotherapy (containing anthracycline, taxane, or both) to receive standard postsurgical treatment either with capecitabine or without (control). The primary end point was disease-free survival. Secondary end points included overall survival. ResultsThe result of the prespecified interim analysis met the primary end point, so this trial was terminated early. The final analysis showed that disease-free survival was longer in the capecitabine group than in the control group (74.1% vs. 67.6% of the patients were alive and free from recurrence or second cancer at 5 years; hazard ratio for recurrence, second cancer, or death, 0.70; 95% ...
TL;DR: Ultraviolet damage in perovskite photovoltaics induced by TiO2 in the electron-transporting layer can be avoided with La-doped BaSnO3, and a low-temperature colloidal method for depositing La- doped Ba SnO3 films as a replacement forTiO2 is reported to reduce such ultraviolet-induced damage.
Abstract: Perovskite solar cells (PSCs) exceeding a power conversion efficiency (PCE) of 20% have mainly been demonstrated by using mesoporous titanium dioxide (mp-TiO2) as an electron-transporting layer. However, TiO2 can reduce the stability of PSCs under illumination (including ultraviolet light). Lanthanum (La)–doped BaSnO3 (LBSO) perovskite would be an ideal replacement given its electron mobility and electronic structure, but LBSO cannot be synthesized as well-dispersible fine particles or crystallized below 500°C. We report a superoxide colloidal solution route for preparing a LBSO electrode under very mild conditions (below 300°C). The PSCs fabricated with LBSO and methylammonium lead iodide (MAPbI3) show a steady-state power conversion efficiency of 21.2%, versus 19.7% for a mp-TiO2 device. The LBSO-based PSCs could retain 93% of their initial performance after 1000 hours of full-Sun illumination.
TL;DR: The GDML approach enables quantitative molecular dynamics simulations for molecules at a fraction of cost of explicit AIMD calculations, thereby allowing the construction of efficient force fields with the accuracy and transferability of high-level ab initio methods.
Abstract: Using conservation of energy-a fundamental property of closed classical and quantum mechanical systems-we develop an efficient gradient-domain machine learning (GDML) approach to construct accurate molecular force fields using a restricted number of samples from ab initio molecular dynamics (AIMD) trajectories. The GDML implementation is able to reproduce global potential energy surfaces of intermediate-sized molecules with an accuracy of 0.3 kcal mol-1 for energies and 1 kcal mol-1 A-1 for atomic forces using only 1000 conformational geometries for training. We demonstrate this accuracy for AIMD trajectories of molecules, including benzene, toluene, naphthalene, ethanol, uracil, and aspirin. The challenge of constructing conservative force fields is accomplished in our work by learning in a Hilbert space of vector-valued functions that obey the law of energy conservation. The GDML approach enables quantitative molecular dynamics simulations for molecules at a fraction of cost of explicit AIMD calculations, thereby allowing the construction of efficient force fields with the accuracy and transferability of high-level ab initio methods.
TL;DR: The argument for obesity as a chronic relapsing disease process is considered, with food the primary agent, particularly foods that are high in energy density such as fat, or in sugar‐sweetened beverages.
Abstract: This paper considers the argument for obesity as a chronic relapsing disease process. Obesity is viewed from an epidemiological model, with an agent affecting the host and producing disease. Food is the primary agent, particularly foods that are high in energy density such as fat, or in sugar-sweetened beverages. An abundance of food, low physical activity and several other environmental factors interact with the genetic susceptibility of the host to produce positive energy balance. The majority of this excess energy is stored as fat in enlarged, and often more numerous fat cells, but some lipid may infiltrate other organs such as the liver (ectopic fat). The enlarged fat cells and ectopic fat produce and secrete a variety of metabolic, hormonal and inflammatory products that produce damage in organs such as the arteries, heart, liver, muscle and pancreas. The magnitude of the obesity and its adverse effects in individuals may relate to the virulence or toxicity of the environment and its interaction with the host. Thus, obesity fits the epidemiological model of a disease process except that the toxic or pathological agent is food rather than a microbe. Reversing obesity will prevent most of its detrimental effects.
TL;DR: A fully-fledged particle-flow reconstruction algorithm tuned to the CMS detector was developed and has been consistently used in physics analyses for the first time at a hadron collider as mentioned in this paper.
Abstract: The CMS apparatus was identified, a few years before the start of the LHC operation at CERN, to feature properties well suited to particle-flow (PF) reconstruction: a highly-segmented tracker, a fine-grained electromagnetic calorimeter, a hermetic hadron calorimeter, a strong magnetic field, and an excellent muon spectrometer. A fully-fledged PF reconstruction algorithm tuned to the CMS detector was therefore developed and has been consistently used in physics analyses for the first time at a hadron collider. For each collision, the comprehensive list of final-state particles identified and reconstructed by the algorithm provides a global event description that leads to unprecedented CMS performance for jet and hadronic τ decay reconstruction, missing transverse momentum determination, and electron and muon identification. This approach also allows particles from pileup interactions to be identified and enables efficient pileup mitigation methods. The data collected by CMS at a centre-of-mass energy of 8\TeV show excellent agreement with the simulation and confirm the superior PF performance at least up to an average of 20 pileup interactions.
TL;DR: This work presents statistical notes for clinical researchers: Chi-squared test and Fisher’s exact test Open lecture on statistics.
Abstract: 152 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/ by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. Statistical notes for clinical researchers: Chi-squared test and Fisher’s exact test Open lecture on statistics
U. Bhawandeep1, Vardan Khachatryan, Albert M. Sirunyan, Armen Tumasyan +2289 more•Institutions (147)
TL;DR: In this paper, the trigger system consists of two levels designed to select events of potential physics interest from a GHz (MHz) interaction rate of proton-proton (heavy ion) collisions.
Abstract: This paper describes the CMS trigger system and its performance during Run 1 of the LHC. The trigger system consists of two levels designed to select events of potential physics interest from a GHz (MHz) interaction rate of proton-proton (heavy ion) collisions. The first level of the trigger is implemented in hardware, and selects events containing detector signals consistent with an electron, photon, muon, tau lepton, jet, or missing transverse energy. A programmable menu of up to 128 object-based algorithms is used to select events for subsequent processing. The trigger thresholds are adjusted to the LHC instantaneous luminosity during data taking in order to restrict the output rate to 100 kHz, the upper limit imposed by the CMS readout electronics. The second level, implemented in software, further refines the purity of the output stream, selecting an average rate of 400 Hz for offline event storage. The objectives, strategy and performance of the trigger system during the LHC Run 1 are described.
TL;DR: The first molecular dynamics simulation with a machine-learned density functional on malonaldehyde is performed and the authors are able to capture the intramolecular proton transfer process.
Abstract: Last year, at least 30,000 scientific papers used the Kohn-Sham scheme of density functional theory to solve electronic structure problems in a wide variety of scientific fields. Machine learning holds the promise of learning the energy functional via examples, bypassing the need to solve the Kohn-Sham equations. This should yield substantial savings in computer time, allowing larger systems and/or longer time-scales to be tackled, but attempts to machine-learn this functional have been limited by the need to find its derivative. The present work overcomes this difficulty by directly learning the density-potential and energy-density maps for test systems and various molecules. We perform the first molecular dynamics simulation with a machine-learned density functional on malonaldehyde and are able to capture the intramolecular proton transfer process. Learning density models now allows the construction of accurate density functionals for realistic molecular systems.Machine learning allows electronic structure calculations to access larger system sizes and, in dynamical simulations, longer time scales. Here, the authors perform such a simulation using a machine-learned density functional that avoids direct solution of the Kohn-Sham equations.
Johns Hopkins University1, Leipzig University2, Humanitas University3, Korea University4, Yale University5, West Virginia University6, University of Barcelona7, St George's, University of London8, Indiana University9, National Yang-Ming University10, Cleveland Clinic11, Aarhus University12, University at Buffalo13, Imperial College London14, Primary Children's Hospital15, Erasmus University Rotterdam16, Yeshiva University17, Ghent University18, Baylor University19, Virginia Commonwealth University20, Harvard University21, Federal University of São Paulo22, University of California, San Francisco23, Beaumont Hospital24, Boston University25, University of Oklahoma26, Carlos III Health Institute27, University of Michigan28, University of Melbourne29, Saint Louis University30, Université de Montréal31, University of Pennsylvania32, McGill University33, Mayo Clinic34, Lahey Hospital & Medical Center35, Royal Adelaide Hospital36, University of Milan37, University of Toronto38, Loyola University Chicago39, Jikei University School of Medicine40
TL;DR: This 2017 Consensus Statement is to provide a state-of-the-art review of the field of catheter and surgical ablation of AF and to report the findings of a writing group, convened by these five international societies.
Abstract: During the past three decades, catheter and surgical ablation of atrial fibrillation (AF) have evolved from investigational procedures to their current role as effective treatment options for patients with AF. Surgical ablation of AF, using either standard, minimally invasive, or hybrid techniques, is available in most major hospitals throughout the world. Catheter ablation of AF is even more widely available, and is now the most commonly performed catheter ablation procedure.
In 2007, an initial Consensus Statement on Catheter and Surgical AF Ablation was developed as a joint effort of the Heart Rhythm Society (HRS), the European Heart Rhythm Association (EHRA), and the European Cardiac Arrhythmia Society (ECAS).1 The 2007 document was also developed in collaboration with the Society of Thoracic Surgeons (STS) and the American College of Cardiology (ACC). This Consensus Statement on Catheter and Surgical AF Ablation was rewritten in 2012 to reflect the many advances in AF ablation that had occurred in the interim.2 The rate of advancement in the tools, techniques, and outcomes of AF ablation continue to increase as enormous research efforts are focused on the mechanisms, outcomes, and treatment of AF. For this reason, the HRS initiated an effort to rewrite and update this Consensus Statement. Reflecting both the worldwide importance of AF, as well as the worldwide performance of AF ablation, this document is the result of a joint partnership between the HRS, EHRA, ECAS, the Asia Pacific Heart Rhythm Society (APHRS), and the Latin American Society of Cardiac Stimulation and Electrophysiology (Sociedad Latinoamericana de Estimulacion Cardiaca y Electrofisiologia [SOLAECE]). The purpose of this 2017 Consensus Statement is to provide a state-of-the-art review of the field of catheter and surgical ablation of AF and to report the findings of a writing group, convened by these five international societies. The writing group is charged with defining the indications, techniques, and outcomes of AF ablation procedures. Included within this document are recommendations pertinent to the design of clinical trials in the field of AF ablation and the reporting of outcomes, including definitions relevant to this topic.
The writing group is composed of 60 experts representing 11 organizations: HRS, EHRA, ECAS, APHRS, SOLAECE, STS, ACC, American Heart Association (AHA), Canadian Heart Rhythm Society (CHRS), Japanese Heart Rhythm Society (JHRS), and Brazilian Society of Cardiac Arrhythmias (Sociedade Brasileira de Arritmias Cardiacas [SOBRAC]). All the members of the writing group, as well as peer reviewers of the document, have provided disclosure statements for all relationships that might be perceived as real or potential conflicts of interest. All author and peer reviewer disclosure information is provided in Appendix A and Appendix B.
In writing a consensus document, it is recognized that consensus does not mean that there was complete agreement among all the writing group members. Surveys of the entire writing group were used to identify areas of consensus concerning performance of AF ablation procedures and to develop recommendations concerning the indications for catheter and surgical AF ablation. These recommendations were systematically balloted by the 60 writing group members and were approved by a minimum of 80% of these members. The recommendations were also subject to a 1-month public comment period. Each partnering and collaborating organization then officially reviewed, commented on, edited, and endorsed the final document and recommendations.
The grading system for indication of class of evidence level was adapted based on that used by the ACC and the AHA.3,4 It is important to state, however, that this document is not a guideline. The indications for catheter and surgical ablation of AF, as well as recommendations for procedure performance, are presented with a Class and Level of Evidence (LOE) to be consistent with what the reader is familiar with seeing in guideline statements. A Class I recommendation means that the benefits of the AF ablation procedure markedly exceed the risks, and that AF ablation should be performed; a Class IIa recommendation means that the benefits of an AF ablation procedure exceed the risks, and that it is reasonable to perform AF ablation; a Class IIb recommendation means that the benefit of AF ablation is greater or equal to the risks, and that AF ablation may be considered; and a Class III recommendation means that AF ablation is of no proven benefit and is not recommended.
The writing group reviewed and ranked evidence supporting current recommendations with the weight of evidence ranked as Level A if the data were derived from high-quality evidence from more than one randomized clinical trial, meta-analyses of high-quality randomized clinical trials, or one or more randomized clinical trials corroborated by high-quality registry studies. The writing group ranked available evidence as Level B-R when there was moderate-quality evidence from one or more randomized clinical trials, or meta-analyses of moderate-quality randomized clinical trials. Level B-NR was used to denote moderate-quality evidence from one or more well-designed, well-executed nonrandomized studies, observational studies, or registry studies. This designation was also used to denote moderate-quality evidence from meta-analyses of such studies. Evidence was ranked as Level C-LD when the primary source of the recommendation was randomized or nonrandomized observational or registry studies with limitations of design or execution, meta-analyses of such studies, or physiological or mechanistic studies of human subjects. Level C-EO was defined as expert opinion based on the clinical experience of the writing group.
Despite a large number of authors, the participation of several societies and professional organizations, and the attempts of the group to reflect the current knowledge in the field adequately, this document is not intended as a guideline. Rather, the group would like to refer to the current guidelines on AF management for the purpose of guiding overall AF management strategies.5,6 This consensus document is specifically focused on catheter and surgical ablation of AF, and summarizes the opinion of the writing group members based on an extensive literature review as well as their own experience. It is directed to all health care professionals who are involved in the care of patients with AF, particularly those who are caring for patients who are undergoing, or are being considered for, catheter or surgical ablation procedures for AF, and those involved in research in the field of AF ablation. This statement is not intended to recommend or promote catheter or surgical ablation of AF. Rather, the ultimate judgment regarding care of a particular patient must be made by the health care provider and the patient in light of all the circumstances presented by that patient.
The main objective of this document is to improve patient care by providing a foundation of knowledge for those involved with catheter ablation of AF. A second major objective is to provide recommendations for designing clinical trials and reporting outcomes of clinical trials of AF ablation. It is recognized that this field continues to evolve rapidly. As this document was being prepared, further clinical trials of catheter and surgical ablation of AF were under way.
TL;DR: In this paper, an improved jet energy scale corrections, based on a data sample corresponding to an integrated luminosity of 19.7 fb^(-1) collected by the CMS experiment in proton-proton collisions at a center-of-mass energy of 8 TeV, are presented.
Abstract: Improved jet energy scale corrections, based on a data sample corresponding to an integrated luminosity of 19.7 fb^(-1) collected by the CMS experiment in proton-proton collisions at a center-of-mass energy of 8 TeV, are presented. The corrections as a function of pseudorapidity η and transverse momentum p_T are extracted from data and simulated events combining several channels and methods. They account successively for the effects of pileup, uniformity of the detector response, and residual data-simulation jet energy scale differences. Further corrections, depending on the jet flavor and distance parameter (jet size) R, are also presented. The jet energy resolution is measured in data and simulated events and is studied as a function of pileup, jet size, and jet flavor. Typical jet energy resolutions at the central rapidities are 15–20% at 30 GeV, about 10% at 100 GeV, and 5% at 1 TeV. The studies exploit events with dijet topology, as well as photon+jet, Z+jet and multijet events. Several new techniques are used to account for the various sources of jet energy scale corrections, and a full set of uncertainties, and their correlations, are provided. The final uncertainties on the jet energy scale are below 3% across the phase space considered by most analyses (p_T > 30 GeV and 0|η| 30 GeV is reached, when excluding the jet flavor uncertainties, which are provided separately for different jet flavors. A new benchmark for jet energy scale determination at hadron colliders is achieved with 0.32% uncertainty for jets with p_T of the order of 165–330 GeV, and |η| < 0.8.
King's College London1, Karolinska Institutet2, Bellvitge University Hospital3, Nihon University4, Trinity College, Dublin5, Kunming Medical University6, Imperial College London7, Brown University8, University of Sheffield9, Otto-von-Guericke University Magdeburg10, Stanford University11, University Hospital Heidelberg12, Korea University13, University of Edinburgh14, Dartmouth College15, University of Amsterdam16, University of Sydney17, National Institutes of Health18, University of Cambridge19, Newcastle University20, University of Pittsburgh21, University of New South Wales22, Janssen Pharmaceutica23, University of Texas Health Science Center at Houston24, Royal Edinburgh Hospital25, University Medical Center Groningen26, Leiden University Medical Center27, VU University Medical Center28, University of East London29
TL;DR: The results suggest that MDD and BD are characterised by both common and distinct patterns of grey-matter volume changes, which has the potential to inform the development of diagnostic biomarkers for these conditions.
Abstract: Finding robust brain substrates of mood disorders is an important target for research. The degree to which major depression (MDD) and bipolar disorder (BD) are associated with common and/or distinct patterns of volumetric changes is nevertheless unclear. Furthermore, the extant literature is heterogeneous with respect to the nature of these changes. We report a meta-analysis of voxel-based morphometry (VBM) studies in MDD and BD. We identified studies published up to January 2015 that compared grey matter in MDD (50 data sets including 4101 individuals) and BD (36 data sets including 2407 individuals) using whole-brain VBM. We used statistical maps from the studies included where available and reported peak coordinates otherwise. Group comparisons and conjunction analyses identified regions in which the disorders showed common and distinct patterns of volumetric alteration. Both disorders were associated with lower grey-matter volume relative to healthy individuals in a number of areas. Conjunction analysis showed smaller volumes in both disorders in clusters in the dorsomedial and ventromedial prefrontal cortex, including the anterior cingulate cortex and bilateral insula. Group comparisons indicated that findings of smaller grey-matter volumes relative to controls in the right dorsolateral prefrontal cortex and left hippocampus, along with cerebellar, temporal and parietal regions were more substantial in major depression. These results suggest that MDD and BD are characterised by both common and distinct patterns of grey-matter volume changes. This combination of differences and similarities has the potential to inform the development of diagnostic biomarkers for these conditions.
TL;DR: In this paper, the authors use the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) to improve and expand the quantification of personal health-care access and quality for 195 countries and territories from 1990 to 2015.
TL;DR: In this article, the authors discuss how 2D transition metal carbides have emerged as efficient and economical nanomaterials for future energy applications and highlight the promising potential of these materials in energy conversion and storage applications, such as water electrolyzers, lithium ion batteries and supercapacitors.
Abstract: The development of two-dimensional (2D) high-performance electrode materials is the key to new advances in the fields of energy conversion and storage. MXenes, a new intriguing family of 2D transition metal carbides, nitrides, and carbonitrides, have recently received considerable attention due to their unique combination of properties such as high electrical conductivity, hydrophilic nature, excellent thermal stability, large interlayer spacing, easily tunable structure, and high surface area. In this review, we discuss how 2D MXenes have emerged as efficient and economical nanomaterials for future energy applications. We highlight the promising potential of these materials in energy conversion and storage applications, such as water electrolyzers, lithium ion batteries, and supercapacitors. Finally, we present an outlook of the future development of MXenes for sustainable energy technologies.
TL;DR: This work introduces HIRA data as an important source for health research and provides guidelines for researchers who are currently utilizing HIRA, or interested in doing so, to answer their research questions, and presents the characteristics and structure ofHIRA data.
Abstract: Health Insurance and Review Assessment (HIRA) in South Korea, also called National Health Insurance (NHI) data, is a repository of claims data collected in the process of reimbursing healthcare providers. Under the universal coverage system, having fee-for-services covering all citizens in South Korea, HIRA contains comprehensive and rich information pertaining to healthcare services such as treatments, pharmaceuticals, procedures, and diagnoses for almost 50 million beneficiaries. This corpus of HIRA data, which constitutes a large repository of data in the healthcare sector, has enormous potential to create value in several ways: enhancing the efficiency of the healthcare delivery system without compromising quality of care; adding supporting evidence for a given intervention; and providing the information needed to prevent (or monitor) adverse events. In order to actualize this potential, HIRA data need to actively be utilized for research. Thus understanding this data would greatly enhance this potential. We introduce HIRA data as an important source for health research and provide guidelines for researchers who are currently utilizing HIRA, or interested in doing so, to answer their research questions. We present the characteristics and structure of HIRA data. We discuss strengths and limitations that should be considered in conducting research with HIRA data and suggest strategies for optimal utilization of HIRA data by reviewing published research using HIRA data.
TL;DR: This review highlights the recent trends in the development of fluorescent materials as essential tools for tracing pH variations in the biological processes of diverse living systems.
Abstract: Protons play crucial roles in many physiological and pathological processes, such as receptor-mediated signal transduction, ion transport, endocytosis, homeostasis, cell proliferation, and apoptosis. The urgent demand for pH imaging and measurement in biological systems has incited the development of fluorescent pH probes. Numerous fluorescent probes have been reported, but many lack the abilities needed for biological applications. Hence, the development of new pH probes with better biocompatibility, sensitivity, and site-specificity is still indispensable. This review highlights the recent trends in the development of fluorescent materials as essential tools for tracing pH variations in the biological processes of diverse living systems.
TL;DR: The first measurement of the tau lepton polarization P-tau(D*) in the decay (B) over bar -> D* tau(-) (v) over b (tau) as well as a new measurement of the ratio of the branching fractions was reported in this paper.
Abstract: We report the first measurement of the tau lepton polarization P-tau(D*) in the decay (B) over bar -> D* tau(-) (v) over bar (tau) as well as a newmeasurement of the ratio of the branching fractions R(D*) = B((B) over bar -> D* tau(-) (v) over bar (tau)) / B((B) over bar -> D* l(-) (v) over bar (l)), where l(-) denotes an electron or a muon, and the tau is reconstructed in the modes tau(-) -> pi(-) v(tau) and tau(-) -> rho(-) v(tau). We use the full data sample of 772 x 10(6) B (B) over bar pairs recorded with the Belle detector at the (KEKB) over bar electron-positron collider. Our results, P-tau(D*) = -0.38 +/- 0.51 (stat)(-0.16)(+0.21) (syst) and R(D*) = 0.270 +/- 0.035 (stat)(- 0.025)(+0.028) (syst), are consistent with the theoretical predictions of the standard model.
TL;DR: This review elucidates the links among catalytic performances, physicochemical properties, and pyrolysis/modification-induced features, advising the tailored production of application-oriented biochar-based catalyst in the future.
TL;DR: A unifying framework for energy-efficient optimization and scheduling of IoT-based smart cities and the energy harvesting in smart cities is provided, which is a promising solution for extending the lifetime of low-power devices and its related challenges.
Abstract: The drastic increase in urbanization over the past few years requires sustainable, efficient, and smart solutions for transportation, governance, environment, quality of life, and so on. The Internet of Things offers many sophisticated and ubiquitous applications for smart cities. The energy demand of IoT applications is increased, while IoT devices continue to grow in both numbers and requirements. Therefore, smart city solutions must have the ability to efficiently utilize energy and handle the associated challenges. Energy management is considered as a key paradigm for the realization of complex energy systems in smart cities. In this article, we present a brief overview of energy management and challenges in smart cities. We then provide a unifying framework for energy-efficient optimization and scheduling of IoT-based smart cities. We also discuss the energy harvesting in smart cities, which is a promising solution for extending the lifetime of low-power devices and its related challenges. We detail two case studies. The first one targets energy-efficient scheduling in smart homes, and the second covers wireless power transfer for IoT devices in smart cities. Simulation results for the case studies demonstrate the tremendous impact of energy- efficient scheduling optimization and wireless power transfer on the performance of IoT in smart cities.