861 research outputs found
Supporting the design of sequences of cumulative activities impacting on multiple areas through a data mining approach : application to design of cognitive rehabilitation programs for traumatic brain injury patients
Traumatic brain injury (TBI) is a leading cause of disability worldwide. It is the most common cause of death and disability during the first three decades of life and accounts for more productive years of life lost than cancer, cardiovascular disease and HIV/AIDS combined. Cognitive Rehabilitation (CR), as part of Neurorehabilitation, aims to reduce the cognitive deficits caused by TBI. CR treatment consists of sequentially organized tasks that require repetitive use of impaired cognitive functions. While task repetition is not the only important feature, it is becoming clear that neuroplastic change and functional improvement only occur after a number of specific tasks are performed in a certain order and repetitions and does not occur otherwise. Until now, there has been an important lack of well-established criteria and on-field experience by which to identify the right number and order of tasks to propose to each individual patient. This thesis proposes the CMIS methodology to support health professionals to compose CR programs by selecting the most promising tasks in the right order. Two contributions to this topic were developed for specific steps of CMIS through innovative data mining techniques SAIMAP and NRRMR methodologies. SAIMAP (Sequence of Activities Improving Multi-Area Performance) proposes an innovative combination of data mining techniques in a hybrid generic methodological framework to find sequential patterns of a predefined set of activities and to associate them with multi-criteria improvement indicators regarding a predefined set of areas targeted by the activities. It combines data and prior knowledge with preprocessing, clustering, motif discovery and classes` post-processing to understand the effects of a sequence of activities on targeted areas, provided that these activities have high interactions and cumulative effects. Furthermore, this work introduces and defines the Neurorehabilitation Range (NRR) concept to determine the degree of performance expected for a CR task and the number of repetitions required to produce maximum rehabilitation effects on the individual. An operationalization of NRR is proposed by means of a visualization tool called SAP. SAP (Sectorized and Annotated Plane) is introduced to identify areas where there is a high probability of a target event occurring. Three approaches to SAP are defined, implemented, applied, and validated to a real case: Vis-SAP, DT-SAP and FT-SAP. Finally, the NRRMR (Neurorehabilitation Range Maximal Regions) problem is introduced as a generalization of the Maximal Empty Rectangle problem (MER) to identify maximal NRR over a FT-SAP. These contributions combined together in the CMIS methodology permit to identify a convenient pattern for a CR program (by means of a regular expression) and to instantiate by a real sequence of tasks in NRR by maximizing expected improvement of patients, thus provide support for the creation of CR plans. First of all, SAIMAP provides the general structure of successful CR sequences providing the length of the sequence and the kind of task recommended at every position (attention tasks, memory task or executive function task). Next, NRRMR provides specific tasks information to help decide which particular task is placed at each position in the sequence, the number of repetitions, and the expected range of results to maximize improvement after treatment. From the Artificial Intelligence point of view the proposed methodologies are general enough to be applied in similar problems where a sequence of interconnected activities with cumulative effects are used to impact on a set of areas of interest, for example spinal cord injury patients following physical rehabilitation program or elderly patients facing cognitive decline due to aging by cognitive stimulation programs or on educational settings to find the best way to combine mathematical drills in a program for a specific Mathematics course.El traumatismo craneoencefálico (TCE) es una de las principales causas de morbilidad y discapacidad a nivel mundial. Es la causa más común de muerte y discapacidad en personas menores de 30 años y es responsable de la pérdida de más años de vida productiva que el cáncer, las enfermedades cardiovasculares y el SIDA sumados. La Rehabilitación Cognitiva (RC) como parte de la Neurorehabilitación, tiene como objetivo reducir el impacto de las condiciones de discapacidad y disminuir los déficits cognitivos causados (por ejemplo) por un TCE. Un tratamiento de RC está formado por un conjunto de tareas organizadas de forma secuencial que requieren un uso repetitivo de las funciones cognitivas afectadas. Mientras que el número de ejecuciones de una tarea no es la única característica importante, es cada vez más evidente que las transformaciones neuroplásticas ocurren cuando se ejecutan un número específico de tareas en un cierto orden y no ocurren en caso contrario. Esta tesis propone la metodología CMIS para dar soporte a los profesionales de la salud en la composición de programas de RC, seleccionando las tareas más prometedoras en el orden correcto. Se han desarrollado dos contribuciones para CMIS mediante las metodologías SAMDMA y RNRRM basadas en técnicas innovadoras de minería de datos. SAMDMA (Secuencias de Actividades que Mejoran el Desempeño en Múltiples Áreas) propone una combinación de técnicas de minería de datos y un marco de trabajo genérico híbrido para encontrar patrones secuenciales en un conjunto de actividades y asociarlos con indicadores de mejora multi-criterio en relación a un conjunto de áreas hacia las cuales las actividades están dirigidas. Combina el uso de datos y conocimiento experto con técnicas de pre-procesamiento, clustering, descubrimiento de motifs y post procesamiento de clases. Además, se introduce y define el concepto de Rango de NeuroRehabilitación (RNR) para determinar el grado de performance esperado para una tarea de RC y el número de repeticiones que debe ejecutarse para producir mayores efectos rehabilitadores. Se propone una operacionalización del RNR por medio de una herramienta de visualización llamada Plano Sectorizado Anotado (PAS). PAS permite identificar áreas en las que hay una alta probabilidad de que ocurra un evento. Tres enfoques diferentes al PAS se definen, implementan, aplican y validan en un caso real : Vis-PAS, DT-PAS y FT-PAS. Finalmente, el problema RNRRM (Rango de NeuroRehabilitación de Regiones Máximas) se presenta como una generalización del problema del Máximo Rectángulo Vacío para identificar RNR máximos sobre un FT-PAS. La combinación de estas dos contribuciones en la metodología CMIS permite identificar un patrón conveniente para un programa de RC (por medio de una expresión regular) e instanciarlo en una secuencia real de tareas en RNR maximizando las mejoras esperadas de los pacientes, proporcionando soporte a la creación de planes de RC. Inicialmente, SAMDMA proporciona la estructura general de secuencias de RC exitosas para cada paciente, proporcionando el largo de la secuencia y el tipo de tarea recomendada en cada posición. RNRRM proporciona información específica de tareas para ayudar a decidir cuál se debe ejecutar en cada posición de la secuencia, el número de veces que debe ser repetida y el rango esperado de resultados para maximizar la mejora. Desde el punto de vista de la Inteligencia Artificial, ambas metodologías propuestas, son suficientemente generales como para ser aplicadas a otros problemas de estructura análoga en que una secuencia de actividades interconectadas con efectos acumulativos se utilizan para impactar en un conjunto de áreas de interés. Por ejemplo pacientes lesionados medulares en tratamiento de rehabilitación física, personas mayores con deterioro cognitivo debido al envejecimiento y utilizan programas de estimulación cognitiva, o entornos educacionales para combinar ejercicios de cálculo en un programa específico de Matemáticas
Know an Emotion by the Company It Keeps: Word Embeddings from Reddit/Coronavirus
Social media is a crucial communication tool (e.g., with 430 million monthly active users in online forums such as Reddit), being an objective of Natural Language Processing (NLP) techniques. One of them (word embeddings) is based on the quotation, “You shall know a word by the company it keeps,” highlighting the importance of context in NLP. Meanwhile, “Context is everything in Emotion Research.” Therefore, we aimed to train a model (W2V) for generating word associations (also known as embeddings) using a popular Coronavirus Reddit forum, validate them using public evidence and apply them to the discovery of context for specific emotions previously reported as related to psychological resilience. We used Pushshiftr, quanteda, broom, wordVectors, and superheat R packages. We collected all 374,421 posts submitted by 104,351 users to Reddit/Coronavirus forum between January 2020 and July 2021. W2V identified 64 terms representing the context for seven positive emotions (gratitude, compassion, love, relief, hope, calm, and admiration) and 52 terms for seven negative emotions (anger, loneliness, boredom, fear, anxiety, confusion, sadness) all from valid experienced situations. We clustered them visually, highlighting contextual similarity. Although trained on a “small” dataset, W2V can be used for context discovery to expand on concepts such as psychological resilience
Personalized Web-Based Cognitive Rehabilitation Treatments for Patients with Traumatic Brain Injury : Cluster Analysis
Funding: This study was partially funded by the INNOBRAIN project: New Technologies for Innovation in Cognitive Stimulation and Rehabilitation (COMRDI15-1-0017). ACCIÓ-Comunitat RIS3CAT d'innovació en salut NEXTHEALTH (COM15-1-0004) cofinanced this project under the FEDER Catalonia 2014-2020 Operational ProgramTraumatic brain injury (TBI) is a leading cause of disability worldwide. TBI is a highly heterogeneous disease, which makes it complex for effective therapeutic interventions. Cluster analysis has been extensively applied in previous research studies to identify homogeneous subgroups based on performance in neuropsychological baseline tests. Nevertheless, most analyzed samples are rarely larger than a size of 100, and different cluster analysis approaches and cluster validity indices have been scarcely compared or applied in web-based rehabilitation treatments. The aims of our study were as follows: (1) to apply state-of-the-art cluster validity indices to different cluster strategies: hierarchical, partitional, and model-based, (2) to apply combined strategies of dimensionality reduction by using principal component analysis and random forests and perform stability assessment of the final profiles, (3) to characterize the identified profiles by using demographic and clinically relevant variables, and (4) to study the external validity of the obtained clusters by considering 3 relevant aspects of TBI rehabilitation: Glasgow Coma Scale, functional independence measure, and execution of web-based cognitive tasks. This study was performed from August 2008 to July 2019. Different cluster strategies were executed with Mclust, factoextra, and cluster R packages. For combined strategies, we used the FactoMineR and random forest R packages. Stability analysis was performed with the fpc R package. Between-group comparisons for external validation were performed using 2-tailed t test, chi-square test, or Mann-Whitney U test, as appropriate. We analyzed 574 adult patients with TBI (mostly severe) who were undergoing web-based rehabilitation. We identified and characterized 3 clusters with strong internal validation: (1) moderate attentional impairment and moderate dysexecutive syndrome with mild memory impairment and normal spatiotemporal perception, with almost 66% (111/170) of the patients being highly educated (P <.05); (2) severe dysexecutive syndrome with severe attentional and memory impairments and normal spatiotemporal perception, with 49.2% (153/311) of the patients being highly educated (P <.05); (3) very severe cognitive impairment, with 45.2% (42/93) of the patients being highly educated (P <.05). We externally validated them with severity of injury (P =.006) and functional independence assessments: cognitive (P <.001), motor (P <.001), and total (P <.001). We mapped 151,763 web-based cognitive rehabilitation tasks during the whole period to the 3 obtained clusters (P <.001) and confirmed the identified patterns. Stability analysis indicated that clusters 1 and 2 were respectively rated as 0.60 and 0.75; therefore, they were measuring a pattern and cluster 3 was rated as highly stable. Cluster analysis in web-based cognitive rehabilitation treatments enables the identification and characterization of strong response patterns to neuropsychological tests, external validation of the obtained clusters, tailoring of cognitive web-based tasks executed in the web platform to the identified profiles, thereby providing clinicians a tool for treatment personalization, and the extension of a similar approach to other medical conditions
Can Integrated Care Help in Meeting the Challenges Posed on Our Health Care Systems by COVID-19? Some Preliminary Lessons Learned from the European VIGOUR Project
The COVID-19 pandemic puts health and care systems under pressure globally. This current paper highlights challenges arising in the care for older and vulnerable populations in this context and reflects upon possible perspectives for different systems making use of nested integrated care approaches adapted during the work of the EU-funded project VIGOU
Les droits disciplinaires des fonctions publiques : « unification », « harmonisation » ou « distanciation ». A propos de la loi du 26 avril 2016 relative à la déontologie et aux droits et obligations des fonctionnaires
The production of tt‾ , W+bb‾ and W+cc‾ is studied in the forward region of proton–proton collisions collected at a centre-of-mass energy of 8 TeV by the LHCb experiment, corresponding to an integrated luminosity of 1.98±0.02 fb−1 . The W bosons are reconstructed in the decays W→ℓν , where ℓ denotes muon or electron, while the b and c quarks are reconstructed as jets. All measured cross-sections are in agreement with next-to-leading-order Standard Model predictions.The production of , and is studied in the forward region of proton-proton collisions collected at a centre-of-mass energy of 8 TeV by the LHCb experiment, corresponding to an integrated luminosity of 1.98 0.02 \mbox{fb}^{-1}. The bosons are reconstructed in the decays , where denotes muon or electron, while the and quarks are reconstructed as jets. All measured cross-sections are in agreement with next-to-leading-order Standard Model predictions
Multidifferential study of identified charged hadron distributions in -tagged jets in proton-proton collisions at 13 TeV
Jet fragmentation functions are measured for the first time in proton-proton
collisions for charged pions, kaons, and protons within jets recoiling against
a boson. The charged-hadron distributions are studied longitudinally and
transversely to the jet direction for jets with transverse momentum 20 GeV and in the pseudorapidity range . The
data sample was collected with the LHCb experiment at a center-of-mass energy
of 13 TeV, corresponding to an integrated luminosity of 1.64 fb. Triple
differential distributions as a function of the hadron longitudinal momentum
fraction, hadron transverse momentum, and jet transverse momentum are also
measured for the first time. This helps constrain transverse-momentum-dependent
fragmentation functions. Differences in the shapes and magnitudes of the
measured distributions for the different hadron species provide insights into
the hadronization process for jets predominantly initiated by light quarks.Comment: All figures and tables, along with machine-readable versions and any
supplementary material and additional information, are available at
https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-013.html (LHCb
public pages
Study of the decay
The decay is studied
in proton-proton collisions at a center-of-mass energy of TeV
using data corresponding to an integrated luminosity of 5
collected by the LHCb experiment. In the system, the
state observed at the BaBar and Belle experiments is
resolved into two narrower states, and ,
whose masses and widths are measured to be where the first uncertainties are statistical and the second
systematic. The results are consistent with a previous LHCb measurement using a
prompt sample. Evidence of a new
state is found with a local significance of , whose mass and width
are measured to be and , respectively. In addition, evidence of a new decay mode
is found with a significance of
. The relative branching fraction of with respect to the
decay is measured to be , where the first
uncertainty is statistical, the second systematic and the third originates from
the branching fractions of charm hadron decays.Comment: All figures and tables, along with any supplementary material and
additional information, are available at
https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-028.html (LHCb
public pages
Measurement of the ratios of branching fractions and
The ratios of branching fractions
and are measured, assuming isospin symmetry, using a
sample of proton-proton collision data corresponding to 3.0 fb of
integrated luminosity recorded by the LHCb experiment during 2011 and 2012. The
tau lepton is identified in the decay mode
. The measured values are
and
, where the first uncertainty is
statistical and the second is systematic. The correlation between these
measurements is . Results are consistent with the current average
of these quantities and are at a combined 1.9 standard deviations from the
predictions based on lepton flavor universality in the Standard Model.Comment: All figures and tables, along with any supplementary material and
additional information, are available at
https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-039.html (LHCb
public pages
Measurement of the J/ψ pair production cross-section in pp collisions at TeV
The production cross-section of J/ψ pairs is measured using a data sample of pp collisions collected by the LHCb experiment at a centre-of-mass energy of TeV, corresponding to an integrated luminosity of 279 ±11 pb. The measurement is performed for J/ψ mesons with a transverse momentum of less than 10 GeV/c in the rapidity range 2.0 < y < 4.5. The production cross-section is measured to be 15.2 ± 1.0 ± 0.9 nb. The first uncertainty is statistical, and the second is systematic. The differential cross-sections as functions of several kinematic variables of the J/ψ pair are measured and compared to theoretical predictions.The production cross-section of pairs is measured using a data sample of collisions collected by the LHCb experiment at a centre-of-mass energy of , corresponding to an integrated luminosity of . The measurement is performed for mesons with a transverse momentum of less than in the rapidity range . The production cross-section is measured to be . The first uncertainty is statistical, and the second is systematic. The differential cross-sections as functions of several kinematic variables of the pair are measured and compared to theoretical predictions
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