pinecone/core-2020-05-10-deduplication huggingface dataset:
An overview of emerging pattern mining in supervised descriptive rule discovery: taxonomy, empirical study, trends, and prospects

Emerging pattern mining is a data mining task that aims to discover discriminative patterns, which can describe emerging behavior with respect to a property of interest. In recent years, the description of datasets has become an interesting field due to the easy acquisition of knowledge by the experts. In this review, we will focus on the descriptive point of view of the task. We collect the existing approaches that have been proposed in the literature and group them together in a taxonomy in order to obtain a general vision of the task. A complete empirical study demonstrates the suitability of the approaches presented. This review also presents future trends and emerging prospects within pattern mining and the benefits of knowledge extracted from emerging patternsSpanish Ministry of Economy and Competitiveness under the project\ud
TIN2015-68454-R (FEDER Founds
Anomaly Detection by Robust Statistics

Real data often contain anomalous cases, also known as outliers. These may
spoil the resulting analysis but they may also contain valuable information. In
either case, the ability to detect such anomalies is essential. A useful tool
for this purpose is robust statistics, which aims to detect the outliers by
first fitting the majority of the data and then flagging data points that
deviate from it. We present an overview of several robust methods and the
resulting graphical outlier detection tools. We discuss robust procedures for
univariate, low-dimensional, and high-dimensional data, such as estimating
location and scatter, linear regression, principal component analysis,
classification, clustering, and functional data analysis. Also the challenging
new topic of cellwise outliers is introduced.Comment: To appear in WIREs Data Mining and Knowledge Discover
Deep learning for remote sensing image classification: : A survey

Remote sensing (RS) image classification plays an important role in the earth observation technology using RS data, having been widely exploited in both military and civil fields. However, due to the characteristics of RS data such as high dimensionality and relatively small amounts of labeled samples available, performing RS image classification faces great scientific and practical challenges. In recent years, as new deep learning (DL) techniques emerge, approaches to RS image classification with DL have achieved significant breakthroughs, offering novel opportunities for the research and development of RS image classification. In this paper, a brief overview of typical DL models is presented first. This is followed by a systematic review of pixel?wise and scene?wise RS image classification approaches that are based on the use of DL. A comparative analysis regarding the performances of typical DL?based RS methods is also provided. Finally, the challenges and potential directions for further research are discussedpublishersversionPeer reviewe
Similarity-based data mining in files of two-dimensional chemical structures using fingerprint measures of molecular resemblance

This paper reviews the use of measures of intermolecular similarity for processing databases of chemical structures, which play an important role in the discovery of new drugs by the pharmaceutical industry. The similarity measures considered here are based on the use of a fingerprint representation of molecular structure, where a fingerprint is a vector encoding the presence of fragment substructures in a molecule and where the similarity between pairs of such fingerprints is computed using an association coefficient such as the Tanimoto coefficient. The Similar Property Principle provides the basic rationale for the use of similarity methods in three important chemoinformatics applications—similarity searching, database clustering, and molecular diversity analysis. Similarity searching enables the identification of those molecules in a database that are most similar to a user-defined, biologically active query molecule, with data fusion providing an effective way of combining the results of multiple similarity searches. Cluster analysis, typically using the Jarvis–Patrick, Ward, or divisive k-means clustering methods, enables the cost-effective selection of molecules for biological testing, for property prediction and for investigating database overlap. Molecular diversity analysis, typically using cluster-based, dissimilarity-based, or optimization-based approaches, enables the identification of structurally diverse sets of molecules, so as to ensure that the full chemical space spanned by a database is tested in the search for novel bioactive molecules. © 2011 John Wiley & Sons, Inc. WIREs Data Mining Knowl Discov 2011 1 241–251 DOI: 10.1002/widm.2
Constructing a GDP-based Index for Use as Benchmark

The gross domestic product [GDP] is a fundamental economic indicator that is frequently used as a benchmark for local equity indices.  The widespread appeal of this association is understandable because an equity index, especially if broad, could, like the GDP, also manifest the state of the economy.  At the same time, however, the validity of a direct relation between the two is debatable since the GDP is known to be characteristically different from the typical equity index, however broad.  

In this work, we review some of the key elements that separate the GDP from a typical broad equity index in order to explain why the two cannot be compared directly with each other.  We then incorporate a readily available mapping technique to create a GDP-based index that circumvents their inherent disparities and, thus, enable us to benchmark one against the other.
Portfolio selection models: A review and new directions

Modern Portfolio Theory (MPT) is based upon the classical Markowitz model which uses variance as a risk measure. A generalization of this approach leads to mean-risk models, in which a return distribution is characterized by the expected value of return (desired to be large) and a risk value (desired to be kept small). Portfolio choice is made by solving an optimization problem, in which the portfolio risk is minimized and a desired level of expected return is specified as a constraint. The need to penalize different undesirable aspects of the return distribution led to the proposal of alternative risk measures, notably those penalizing only the downside part (adverse) and not the upside (potential). The downside risk considerations constitute the basis of the Post Modern Portfolio Theory (PMPT). Examples of such risk measures are lower partial moments, Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR). We revisit these risk measures and the resulting mean-risk models. We discuss alternative models for portfolio selection, their choice criteria and the evolution of MPT to PMPT which incorporates: utility maximization and stochastic dominance
Robust performance hypothesis testing with the variance

Applied researchers often test for the difference of the variance of two investment strategies;\ud
in particular, when the investment strategies under consideration aim to implement\ud
the global minimum variance portfolio. A popular tool to this end is the F-test for the\ud
equality of variances. Unfortunately, this test is not valid when the returns are correlated,\ud
have tails heavier than the normal distribution, or are of time series nature. Instead, we\ud
propose the use of robust inference methods. In particular, we suggest to construct a studentized\ud
time series bootstrap confidence interval for the ratio of the two variances and to\ud
declare the two variances different if the value one is not contained in the obtained interval.\ud
This approach has the advantage that one can simply resample from the observed data\ud
as opposed to some null-restricted data. A simulation study demonstrates the improved\ud
finite-sample performance compared to existing methods
HIV and Injecting Drug Users in Vietnam: An Overview of Policies and Responses

The HIV epidemic in Vietnam is fueled by injecting drug use. Since HIV emerged, because of a law-enforcement-focused drug policy and response, injecting drug users (IDUs) frequently experience drug detention and compulsory treatment. It has taken more than a decade to shift the focus from punitive to liberal policies. This overview presents a brief discussion on policies, responses, and experiences to identify implications. Related literature including government policies, peer-reviewed articles, and reports has been reviewed. The HIV epidemic in IDUs accelerated rapidly in an environment characterized by a lack in understanding and recognition of significance. There was limited leadership and weak direction to implement a countrywide response. Policies and responses gradually shifted to a harm reduction approach and recognized the need for harmonization, relating common features of drug and HIV. The review identifies that government leadership is crucial for supportive policies and long-term strategies. A multi-sectoral collaboration and continuous resource allocation with national priorities is essential to impact on the epidemic. In this review the context of these issues in policies and responses are highlighted and discussed, which gradually can lead towards the development of a substantial response for the drug use-driven HIV epidemic in Vietnam.Griffith Health, School of Public HealthFull Tex
Microengineered synthetic cellular microenvironment for stem cells

Stem cells possess the ability of self‐renewal and differentiation into specific cell types. Therefore, stem cells have great potentials in fundamental biology studies and clinical applications. The most urgent desire for stem cell research is to generate appropriate artificial stem cell culture system, which can mimic the dynamic complexity and precise regulation of the  in vivo  biochemical and biomechanical signals, to regulate and direct stem cell behaviors. Precise control and regulation of the biochemical and biomechanical stimuli to stem cells have been successfully achieved using emerging micro/nanoengineering techniques. This review provides insights into how these micro/nanoengineering approaches, particularly microcontact printing and elastomeric micropost array, are applied to create dynamic and complex environment for stem cells culture.  WIREs Nanomed Nanobiotechnol  2012, 4:414–427. doi: 10.1002/wnan.1175  For further resources related to this article, please visit the  WIREs website
High throughput toxicity screening and intracellular detection of nanomaterials

With the growing numbers of nanomaterials (), there is a great demand for rapid and reliable ways of testing safety—preferably using in vitro approaches, to avoid the ethical dilemmas associated with animal research. Data are needed for developing intelligent testing strategies for risk assessment of , based on grouping and read‐across approaches. The adoption of high throughput screening () and high content analysis () for toxicity testing allows the testing of numerous materials at different concentrations and on different types of cells, reduces the effect of inter‐experimental variation, and makes substantial savings in time and cost. / approaches facilitate the classification of key biological indicators of ‐cell interactions. Validation of in vitro tests is required, taking account of relevance to results. / approaches are needed to assess dose‐ and time‐dependent toxicity, allowing prediction of adverse effects. Several / methods are being validated and applied for testing in the project , including Label‐free cellular screening of uptake, HCA, High throughput flow cytometry, Impedance‐based monitoring, Multiplex analysis of secreted products, and genotoxicity methods—namely High throughput comet assay, High throughput in vitro micronucleus assay, and assay. There are several technical challenges with / for testing, as toxicity screening needs to be coupled with characterization of in exposure medium prior to the test; possible interference of with / techniques is another concern. Advantages and challenges of / approaches in safety are discussed
High throughput toxicity screening and intracellular detection of nanomaterials

EC FP7 NANoREG (Grant Agreement NMP4-LA-2013-310584)Free PMC Article: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5215403/With the growing numbers of nanomaterials (NMs), there is a great demand for
rapid and reliable ways of testing NM safety—preferably using in vitro
approaches, to avoid the ethical dilemmas associated with animal research. Data
are needed for developing intelligent testing strategies for risk assessment of
NMs, based on grouping and read-across approaches. The adoption of high
throughput screening (HTS) and high content analysis (HCA) for NM toxicity
testing allows the testing of numerous materials at different concentrations and
on different types of cells, reduces the effect of inter-experimental variation, and
makes substantial savings in time and cost.info:eu-repo/semantics/publishedVersio
Protein corona and nanoparticles: How can we investigate on?

Nanoparticles (NPs) represent one of the most promising tools for drug-targeting and drug-delivery. However, a deeper understanding of the complex dynamics that happen after their in vivo administration is required. Particularly, plasma proteins tend to associate to NPs, forming a new surface named the 'protein corona' (PC). This surface is the most exposed as the 'visible side' of NPs and therefore, can have a strong impact on NP biodistribution, targeting efficacy and also toxicity. The PC consists of two poorly delimited layers, known as 'hard corona' (HC) and 'soft corona' (SC), that are affected by the complexity of the environment and the formed protein-surface equilibrium during in vivo blood circulation. The HC corona is formed by proteins strongly associated to the NPs, while the SC is an outer layer consisting of loosely bound proteins. Several studies attempted to investigate the HC, which is easier to be isolated, but yielded poor reproducibility, due to varying experimental conditions. As a consequence, full mapping of the HC for different NPs is still lacking. Moreover, the current knowledge on the SC, which may play a major role in the 'first' interaction of NPs once in vivo, is very limited, mainly due to the difficulties in preserving it after purification. Therefore, multi-disciplinary approaches leading to the obtainment of a major number of information about the PC and its properties is strongly needed to fully understand its impact and to better support a more safety and conscious application of nanotechnology in medicine
Beyond DNA origami: the unfolding prospects of nucleic acid nanotechnology

Nucleic acid nanotechnology exploits the programmable molecular recognition properties of natural and synthetic nucleic acids to assemble structures with nanometer‐scale precision. In 2006, DNA origami transformed the field by providing a versatile platform for self‐assembly of arbitrary shapes from one long DNA strand held in place by hundreds of short, site‐specific (spatially addressable) DNA ‘staples’. This revolutionary approach has led to the creation of a multitude of two‐dimensional and three‐dimensional scaffolds that form the basis for functional nanodevices. Not limited to nucleic acids, these nanodevices can incorporate other structural and functional materials, such as proteins and nanoparticles, making them broadly useful for current and future applications in emerging fields such as nanomedicine, nanoelectronics, and alternative energy.  WIREs Nanomed Nanobiotechnol  2012, 4:139–152. doi: 10.1002/wnan.170  For further resources related to this article, please visit the  WIREs website
Nanotechnology in joint replacement

El pdf del artículo es la versión post-print.This paper reviews the most relevant achievements and new developments in the field of nanomaterials and their possible impact on the fabrication of a new generation of reliable and longer lasting implants for joint replacement. Special emphasis is given to the role of nanocomposites with different microstructural designs: micro-nano composites, nano-nano composites, macro-micro-nano composites as well as bioinspired hierarchical composite materials. These nanostructured materials have opened up an exciting avenue in the design of non-metallic biocompatible, crack growth resistant, tough, and mechanically resistant implants with a lifespan close to the life expectancy of the patients. Copyright (c) 2009 John Wiley & Sons, Inc.Authors would like to acknowledge the European Commission for its financial support under contract IP Nanoker, Contract number NMP3-CT-2005-515784.Peer Reviewe
Diagnosis and classification of disorders specifically associated with stress: proposals for ICD-11

The diagnostic concepts of post-traumatic stress disorder (PTSD) and other disorders specifically associated with stress have been intensively discussed among neuro- and social scientists, clinicians, epidemiologists, public health planners and humanitarian aid workers around the world. PTSD and adjustment disorder are among the most widely used diagnoses in mental health care worldwide. This paper describes proposals that aim to maximize clinical utility for the classification and grouping of disorders specifically associated with stress in the forthcoming 11th revision of the International Classification of Diseases (ICD-11). Proposals include a narrower concept for PTSD that does not allow the diagnosis to be made based entirely on non-specific symptoms; a new complex PTSD category that comprises three clusters of intra- and interpersonal symptoms in addition to core PTSD symptoms; a new diagnosis of prolonged grief disorder, used to describe patients that undergo an intensely painful, disabling, and abnormally persistent response to bereavement; a major revision of “adjustment disorder” involving increased specification of symptoms; and a conceptualization of “acute stress reaction” as a normal phenomenon that still may require clinical intervention. These proposals were developed with specific considerations given to clinical utility and global applicability in both low- and high-income countries
Psychotic symptoms are associated with physical health problems independently of a mental disorder diagnosis: Results from the WHO World Health Survey

This study explored whether physical health problems are related to psychotic symptoms independently of a mental disorder diagnosis. A total
of 224,254 subjects recruited for the World Health Organization World Health Survey were subdivided into those with both a lifetime diagnosis
of psychosis and at least one psychotic symptom in the 12 months prior to the evaluation, those with at least one psychotic symptom in the
past 12 months but no lifetime diagnosis of psychosis, and those without psychotic symptoms in the past 12 months and without a lifetime
diagnosis of psychosis. The three groups were compared for the presence of medical conditions, health problems, and access to health care.
Medical conditions and health problems (angina, asthma, arthritis, tuberculosis, vision or hearing problems, mouth/teeth problems, alcohol
consumption, smoking, and accidents), medication consumption, and hospital admissions (but not regular health care visits) were more frequent
in individuals with psychotic symptoms but no psychosis diagnosis, compared to those with no symptoms and no diagnosis. The number
of medical conditions increased with the number of psychotic symptoms. Given the sample analyzed, this trend seems to be independent from
the socio-economic development of the country or the specific health care systemThis work was supported by the Spanish Ministry of Economy
and Competitiveness, Instituto de Salud Carlos III,
CIBERSAM, Madrid Regional Government (S2010/BMD-
2422 AGES), European Union Structural Funds, Fundación
Alicia Koplowitz, Fundación Mutua Madrileña, ERA-NET
NEURON (Network of European Funding for Neuroscience
Research) and theWorld Health Organizatio
Novel psychoactive substances of interest for psychiatry

Novel psychoactive substances include synthetic cannabinoids, cathinone derivatives, psychedelic phenethylamines, novel stimulants, synthetic opioids, tryptamine derivatives, phencyclidine-like dissociatives, piperazines, GABA-A/B receptor agonists, a range of prescribedmedications, psychoactive plants/herbs, and a large series of performance and image enhancing drugs. Users are typically attracted by these substances due to their intense psychoactive effects and likely lack of detection in routine drug screenings. This paper aims at providing psychiatrists with updated knowledge of the clinical pharmacology and psychopathological consequences of the use of these substances. Indeed, these drugs act on a range of neurotransmitter pathways/receptors whose imbalance has been associated with psychopathological conditions, including dopamine, cannabinoid CB1, GABA-A/B, 5-HT2A, glutamate, and k opioid receptors. An overall approach in terms of clinical management is briefly discussed
"Prolonged grief disorder" and "persistent complex bereavement disorder", but not "complicated grief", are one and the same diagnostic entity: an analysis of data from the Yale Bereavement Study

There exists a general consensus that prolonged grief disorder (PGD), or some variant of PGD, represents a distinct mental disorder worthy of diagnosis and treatment. Nevertheless, confusion remains over whether different names and proposed symptom criteria for this disorder identify the same or different diagnostic entities. This study aimed to determine whether PGD, complicated grief (CG), and persistent complex bereavement disorder (PCBD) as described by the DSM-5 are substantively or merely semantically different diagnostic entities. Data were derived from the Yale Bereavement Study, a longitudinal community-based study of bereaved individuals funded by the US National Institute of Mental Health, designed explicitly to evaluate diagnostic criteria for disordered grief. The results suggested that the difference between PGD and PCBD is only semantic. The level of agreement between the original PGD test, a new version of the PGD test proposed for ICD-11 and the PCBD test was high (pairwise kappa coefficients = 0.80-0.84). Their estimates of rate of disorder in this community sample were similarly low (∼10%). Their levels of diagnostic specificity were comparably high (95.0-98.3%). Their predictive validity was comparable. In contrast, the test for CG had only moderate agreement with those for PGD and PCBD; its estimate of rate of disorder was three-fold higher (∼30%); its diagnostic specificity was poorer, and it had no predictive validity. We conclude that PGD, PCBD and proposed ICD-11, but not CG, symptom-diagnostic tests identify a single diagnostic entity. Ultimately, brief symptom-diagnostic tests, such as the one proposed here for ICD-11, may have the greatest clinical utility