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Topic modeling is a learning process aiming to analyze texts to discover their topic composition by associating groups of correlated words. Historically, topic modeling has used unsupervised learning techniques. Bayesian generative models, such as Latent Dirichlet Allocation (LDA), have quickly proven their performance for representing with probabilities the distributions of words across topics and of topics across documents. Recently, new topic models based on LDA have emerged, like the Hierarchical Dirichlet Process (HDP) which self-determines the number of topics in the text and the nested Hierarchical Dirichlet Process (nHDP) which enables a hierarchical representation of the topics.

The performances in topic identification and hierarchical modeling of HDP and nHDP were evaluated in this work, on English and French corpora built from Wikipedia articles. A large number of very coherent and interesting topics were detected in both languages, despite the presence of some less coherent ones. Correlations have been highlighted between the statistics of the corpus and evaluation metrics such as coherence and model perplexity.

Additionally, a more recent approach of learning word embeddings in hyperbolic space, specifically in the Poincaré ball space, has been studied to determine if it could constitute a promising approach to hierarchical topic modeling. Poincaré embeddings of 10 dimensions were trained on hypernymy relations of our English corpus. Our analysis revealed clusters of words which can be linked to topics, unfortunately the 2D representation method we applied did not allow to show hierarchical relations between those clusters.

In conclusion, both HDP and nHDP models have shown good and similar learning performances when trained on French and English corpora, nHDP being also efficient in providing hierarchical representation of the topics. The Poincaré embeddings were successful in learning and representing the hypernymy relations in the Poincaré ball, however suffered from the constraints imposed by the data acquisition methods and required filtering processes.

LDA --- HDP --- nHDP --- Poincaré --- embeddings --- topic --- modeling --- Dirichlet --- Ingénierie, informatique & technologie > Sciences informatiques

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Global health, conceived as a discipline, aims to train, research and respond to problems of a transboundary nature, in order to improve health and health equity at the global level. The current worldwide situation is ruled by globalization, and therefore the concept of global health involves not only health-related issues, but also those related to the environment and climate change. Therefore, in this Special Issue, the problems related to global health have been addressed from a bibliometric approach in four main areas: environmental issues, diseases, health, education and society.

social networks --- health --- young people --- bibliometric study --- scientometrics --- obesity --- interventions --- children --- youths --- pediatrics --- reclaimed water --- advanced oxidation process --- microorganisms --- concern emergent contaminant --- worldwide --- content analysis --- text mining --- diabetes --- QOL --- artificial intelligence --- machine learning --- bibliometric --- LDA --- HIV/AIDS --- quality of life --- global health --- public health --- scientometric study --- knowledge map --- visualization analysis --- CiteSpace --- COPD --- QoL --- medicinal plants --- drugs --- worldwide research --- bibliometrics --- traditional medicine --- asthma --- HRQoL --- Scival --- patents --- Spain --- Research and Development (R&amp --- D) --- social returns --- COVID-19 --- biomechanics --- musculoskeletal disorders --- RULA --- ergonomics --- applications --- climate change --- infectious diseases --- bibliometric analysis --- co-word analysis --- biclustering --- strategic diagram --- academic performance --- citation network --- motivation --- microplastics --- network analysis --- VOSviewer software --- research hotspots --- pulmonary disease --- musculoskeletal risks --- wastewater treatment

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Electrical machines and drives dominate our everyday lives. This is due to their numerous applications in industry, power production, home appliances, and transportation systems such as electric and hybrid electric vehicles, ships, and aircrafts. Their development follows rapid advances in science, engineering, and technology. Researchers around the world are extensively investigating electrical machines and drives because of their reliability, efficiency, performance, and fault-tolerant structure. In particular, there is a focus on the importance of utilizing these new trends in technology for energy saving and reducing greenhouse gas emissions. This Special Issue will provide the platform for researchers to present their recent work on advances in the field of electrical machines and drives, including special machines and their applications; new materials, including the insulation of electrical machines; new trends in diagnostics and condition monitoring; power electronics, control schemes, and algorithms for electrical drives; new topologies; and innovative applications.

Technology: general issues --- History of engineering & technology --- fault size --- inter-laminar fault --- localized losses --- thermographic measurement --- thermal-electric coupling --- axial flux --- demagnetization --- finite element analysis --- permanent magnet --- static eccentricity --- synchronous generator --- power loss minimization --- speed control drive systems --- efficiency measurement --- IPMSM --- additive manufacturing --- three-dimensional printing --- topology optimization --- magnetic materials --- soft magnetic materials --- permanent magnets --- electrical machines --- torque ripple --- 6th harmonic --- induction motor --- AC machine --- PWM inverter --- space phasor modulation --- electric motor --- interior permanent magnet --- reluctance --- MMF-permeance --- winding function --- predictive maintenance --- digital twin --- artificial intelligence --- Industry 4.0 --- data handling --- life cycle --- electric machines --- electromagnetic analysis --- electromagnetic measurements --- core losses --- rotor flux linkage --- modular stator --- oriented steel --- flux-injecting probes --- insulation system --- partial discharges --- capacitive model --- MATLAB/Simulink --- flashover voltage --- epoxy resin --- matrix-converter --- input AC filter design --- PMSM --- predictive control --- electrical drives --- energy efficiency --- energy-saving --- power quality --- current signals --- stray flux signals --- LDA --- automatic fault diagnosis --- broken rotor bars --- soft-starters

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Global health, conceived as a discipline, aims to train, research and respond to problems of a transboundary nature, in order to improve health and health equity at the global level. The current worldwide situation is ruled by globalization, and therefore the concept of global health involves not only health-related issues, but also those related to the environment and climate change. Therefore, in this Special Issue, the problems related to global health have been addressed from a bibliometric approach in four main areas: environmental issues, diseases, health, education and society.

Research & information: general --- social networks --- health --- young people --- bibliometric study --- scientometrics --- obesity --- interventions --- children --- youths --- pediatrics --- reclaimed water --- advanced oxidation process --- microorganisms --- concern emergent contaminant --- worldwide --- content analysis --- text mining --- diabetes --- QOL --- artificial intelligence --- machine learning --- bibliometric --- LDA --- HIV/AIDS --- quality of life --- global health --- public health --- scientometric study --- knowledge map --- visualization analysis --- CiteSpace --- COPD --- QoL --- medicinal plants --- drugs --- worldwide research --- bibliometrics --- traditional medicine --- asthma --- HRQoL --- Scival --- patents --- Spain --- Research and Development (R&amp --- D) --- social returns --- COVID-19 --- biomechanics --- musculoskeletal disorders --- RULA --- ergonomics --- applications --- climate change --- infectious diseases --- bibliometric analysis --- co-word analysis --- biclustering --- strategic diagram --- academic performance --- citation network --- motivation --- microplastics --- network analysis --- VOSviewer software --- research hotspots --- pulmonary disease --- musculoskeletal risks --- wastewater treatment

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• Reference Manager
• EndNote
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Electrical machines and drives dominate our everyday lives. This is due to their numerous applications in industry, power production, home appliances, and transportation systems such as electric and hybrid electric vehicles, ships, and aircrafts. Their development follows rapid advances in science, engineering, and technology. Researchers around the world are extensively investigating electrical machines and drives because of their reliability, efficiency, performance, and fault-tolerant structure. In particular, there is a focus on the importance of utilizing these new trends in technology for energy saving and reducing greenhouse gas emissions. This Special Issue will provide the platform for researchers to present their recent work on advances in the field of electrical machines and drives, including special machines and their applications; new materials, including the insulation of electrical machines; new trends in diagnostics and condition monitoring; power electronics, control schemes, and algorithms for electrical drives; new topologies; and innovative applications.

fault size --- inter-laminar fault --- localized losses --- thermographic measurement --- thermal-electric coupling --- axial flux --- demagnetization --- finite element analysis --- permanent magnet --- static eccentricity --- synchronous generator --- power loss minimization --- speed control drive systems --- efficiency measurement --- IPMSM --- additive manufacturing --- three-dimensional printing --- topology optimization --- magnetic materials --- soft magnetic materials --- permanent magnets --- electrical machines --- torque ripple --- 6th harmonic --- induction motor --- AC machine --- PWM inverter --- space phasor modulation --- electric motor --- interior permanent magnet --- reluctance --- MMF-permeance --- winding function --- predictive maintenance --- digital twin --- artificial intelligence --- Industry 4.0 --- data handling --- life cycle --- electric machines --- electromagnetic analysis --- electromagnetic measurements --- core losses --- rotor flux linkage --- modular stator --- oriented steel --- flux-injecting probes --- insulation system --- partial discharges --- capacitive model --- MATLAB/Simulink --- flashover voltage --- epoxy resin --- matrix-converter --- input AC filter design --- PMSM --- predictive control --- electrical drives --- energy efficiency --- energy-saving --- power quality --- current signals --- stray flux signals --- LDA --- automatic fault diagnosis --- broken rotor bars --- soft-starters