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1.
Int J Public Health ; 66: 1604210, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-34483810

RESUMEN

Objectives: In the COVID-19 pandemic, critical health literacy (CHL-P) has been proposed as a means of addressing issues of complexity, uncertainty, and urgency. Our study aimed to identify CHL-P clusters among university students in Germany and to analyze associations with potential determinants. Methods: In May 2020, students at four German universities participated in the COVID-19 International Student Well-Being Study, an online survey that yielded a non-probabilistic sample of N = 5,021. CHL-P, COVID-19-related knowledge, worries, risk perception, and adherence to protective measures were measured in an online questionnaire with self-constructed items. We conducted a cluster analysis of the five CHL-P items and performed logistic regression analyses. Results: Two CHL-P clusters were identified: high vs. moderate CHL-P. Belonging to the high-CHL-P cluster (31.2% of students) was significantly associated with older age, female/other gender, advanced education, higher levels of parental education, and moderate importance placed on education. In addition, higher levels of knowledge, risk perception and worries, and adherence to protective measures were associated with high CHL-P cluster membership. Conclusion: Students would benefit from educational measures that promote CHL-P at German universities.


Asunto(s)
COVID-19 , Alfabetización en Salud , Pandemias , Estudiantes , Adulto , COVID-19/epidemiología , Análisis por Conglomerados , Femenino , Alemania/epidemiología , Alfabetización en Salud/estadística & datos numéricos , Humanos , Masculino , Estudiantes/estadística & datos numéricos , Encuestas y Cuestionarios , Universidades , Adulto Joven
2.
Ann Palliat Med ; 10(8): 8982-8990, 2021 Aug.
Artículo en Inglés | MEDLINE | ID: mdl-34488385

RESUMEN

BACKGROUND: Traditional Chinese medicine (TCM) has shown excellent therapeutic effects in the treatment of heart diseases. This meta-analysis was to evaluate the therapeutic effects of TCM on patients with atrial fibrillation (AF). METHODS: Four databases were searched from their establishment to 1 April 2021 for randomized controlled trials (RCTs) on the treatment of AF using TCM. The Cochrane Handbook 5.0.2 was used to perform to bias risk assessment, and RevMan 5.3 was used for meta-analysis. RESULTS: A total of 7 references were included. It was found that compared with conventional Western medicine, the effective rate of TCM or the combined therapy of TCM and Western medicine was higher [mean difference (MD) =1.85; 95% confidence interval (CI): 1.28 to 2.68; Z=3.26; P=0.001]; the success rate of conversion was increased (MD =1.58; 95% CI: 1.02 to 2.44; Z=2.06; P=0.04), the conversion time was shortened (MD =-224.82; 95% CI: -262.56 to -187.08; Z=11.68; P<0.00001), the incidence of adverse reactions was reduced (MD =0.62; 95% CI: 0.40 to 0.97; Z=2.11; P=0.03). DISCUSSION: The use of TCM to treat AF can improve clinical treatment efficiency, increase the success rate of conversion, and shorten the conversion time. Compared with conventional Western medicine, the combined therapy demonstrated better therapeutic effects.


Asunto(s)
Fibrilación Atrial , Medicina China Tradicional , Fibrilación Atrial/tratamiento farmacológico , Análisis por Conglomerados , Humanos
3.
Comput Intell Neurosci ; 2021: 2675052, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-34512740

RESUMEN

Airport gate assignment performance indicator selection is a complicated decision-making problem with strong subjectivity and difficulty in measuring the importance of each indicator. A better selection of performance indicators (PIs) can greatly increase the airport overall benefit. We adopt a multicriteria decision-making approach to quantify qualitative PIs and conduct subsequent selection using the fuzzy clustering method. First, we identify 21 commonly used PIs through literature review and survey. Subsequently, the fuzzy analytic hierarchy process technique was employed to obtain the selection criteria weights based on the relative importance of significance, availability, and generalisability. Further, we aggregated the selection criteria weights and experts' score to evaluate each PI for the clustering process. The fuzzy-possibilistic product partition c-means algorithm was applied to divide the PIs into different groups based on the three selection criteria as partitioning features. The cluster with highest weights of the centre was identified as the very high-influence cluster, and 10 PIs were identified as a result. This study revealed that the passenger-oriented objective is the most important performance criterion; however, the relevance of the airport/airline-oriented and robustness-oriented performance objectives was highlighted as well. It also offers a scientific approach to determine the objective functions for future gate assignment research. And, we believe, through slight modifications, this model can be used in other airports, other indicator selection problems, or other scenarios at the same airport to facilitate policy making and real situation practice, hence facilitate the management system for the airport.


Asunto(s)
Aeropuertos , Algoritmos , Análisis por Conglomerados , Lógica Difusa
4.
Comput Intell Neurosci ; 2021: 6734345, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-34512744

RESUMEN

Since the reform and opening up, China's regional economy has developed rapidly. However, due to different starting points of economic development caused by the traditional distribution of productive forces and the differences in regions, resources, technologies, and policies, the level of economic development in different regions is uneven. Clustering analysis is a data mining method that clusters or classifies entities according to their characteristics and then discovers the whole spatial distribution law of datasets and typical patterns. It is of great significance to classify, compare, and study the economic development level of different regions in order to formulate the regional economic development strategy. In this paper, a self-organizing feature map (SOM) neural network with the hybrid genetic algorithm is used to cluster the differences of regional economic development, the clustering results are evaluated, and the empirical results are good. From this, some meaningful conclusions can be drawn, which can provide reference for the decision-making of coordinating regional economic development.


Asunto(s)
Desarrollo Económico , Redes Neurales de la Computación , Algoritmos , China , Análisis por Conglomerados , Minería de Datos
5.
Sensors (Basel) ; 21(17)2021 Aug 27.
Artículo en Inglés | MEDLINE | ID: mdl-34502667

RESUMEN

The use of underwater wireless sensor networks (UWSNs) for collaborative monitoring and marine data collection tasks is rapidly increasing. One of the major challenges associated with building these networks is handover prediction; this is because the mobility model of the sensor nodes is different from that of ground-based wireless sensor network (WSN) devices. Therefore, handover prediction is the focus of the present work. There have been limited efforts in addressing the handover prediction problem in UWSNs and in the use of ensemble learning in handover prediction for UWSNs. Hence, we propose the simulation of the sensor node mobility using real marine data collected by the Korea Hydrographic and Oceanographic Agency. These data include the water current speed and direction between data. The proposed simulation consists of a large number of sensor nodes and base stations in a UWSN. Next, we collected the handover events from the simulation, which were utilized as a dataset for the handover prediction task. Finally, we utilized four machine learning prediction algorithms (i.e., gradient boosting, decision tree (DT), Gaussian naive Bayes (GNB), and K-nearest neighbor (KNN)) to predict handover events based on historically collected handover events. The obtained prediction accuracy rates were above 95%. The best prediction accuracy rate achieved by the state-of-the-art method was 56% for any UWSN. Moreover, when the proposed models were evaluated on performance metrics, the measured evolution scores emphasized the high quality of the proposed prediction models. While the ensemble learning model outperformed the GNB and KNN models, the performance of ensemble learning and decision tree models was almost identical.


Asunto(s)
Algoritmos , Tecnología Inalámbrica , Teorema de Bayes , Análisis por Conglomerados , Aprendizaje Automático
6.
Sensors (Basel) ; 21(17)2021 Aug 30.
Artículo en Inglés | MEDLINE | ID: mdl-34502724

RESUMEN

The rapid growth in the industrial sector has required the development of more productive and reliable machinery, and therefore, leads to complex systems. In this regard, the automatic detection of unknown events in machinery represents a greater challenge, since uncharacterized catastrophic faults can occur. However, the existing methods for anomaly detection present limitations when dealing with highly complex industrial systems. For that purpose, a novel fault diagnosis methodology is developed to face the anomaly detection. An unsupervised anomaly detection framework named deep-autoencoder-compact-clustering one-class support-vector machine (DAECC-OC-SVM) is presented, which aims to incorporate the advantages of automatically learnt representation by deep neural network to improved anomaly detection performance. The method combines the training of a deep-autoencoder with clustering compact model and a one-class support-vector-machine function-based outlier detection method. The addressed methodology is applied on a public rolling bearing faults experimental test bench and on multi-fault experimental test bench. The results show that the proposed methodology it is able to accurately to detect unknown defects, outperforming other state-of-the-art methods.


Asunto(s)
Redes Neurales de la Computación , Máquina de Vectores de Soporte , Análisis por Conglomerados , Aprendizaje
7.
Chaos ; 31(8): 083107, 2021 Aug.
Artículo en Inglés | MEDLINE | ID: mdl-34470251

RESUMEN

The firing patterns of each bursting neuron are different because of the heterogeneity, which may be derived from the different parameters or external drives of the same kind of neurons, or even neurons with different functions. In this paper, the different electromagnetic effects produced by two fractional-order memristive (FOM) Hindmarsh-Rose (HR) neuron models are selected for characterizing different firing patterns of heterogeneous neurons. Meanwhile, a fractional-order memristor-coupled heterogeneous memristive HR neural network is constructed via coupling these two heterogeneous FOM HR neuron models, which has not been reported in the adjacent neuron models with memristor coupling. With the study of initial-depending bifurcation behaviors of the system, it is found that the system exhibits abundant hidden firing patterns, such as periods with different topologies, quasiperiodic firings, chaos with different topologies, and even hyperchaotic firings. Particularly, the hidden hyperchaotic firings are perfectly detected by two-dimensional Lyapunov stability graphs in the two-parameter space. Meanwhile, the hidden coexisting firing patterns of the system are excited from two scattered attraction domains, which can be confirmed from the local attraction basins. Furthermore, the color image encryption based on the system and the DNA approach owns great keyspace and a good encryption effect. Finally, the digital implementations based on Advanced RISC Machine are in good coincidence with numerical simulations.


Asunto(s)
Modelos Neurológicos , Redes Neurales de la Computación , Análisis por Conglomerados , Neuronas
8.
BMC Bioinformatics ; 22(1): 422, 2021 Sep 07.
Artículo en Inglés | MEDLINE | ID: mdl-34493215

RESUMEN

BACKGROUND: With more T cell receptor sequence data becoming available, the need for bioinformatics approaches to predict T cell receptor specificity is even more pressing. Here we present SwarmTCR, a method that uses labeled sequence data to predict the specificity of T cell receptors using a nearest-neighbor approach. SwarmTCR works by optimizing the weights of the individual CDR regions to maximize classification performance. RESULTS: We compared the performance of SwarmTCR against another nearest-neighbor method and showed that SwarmTCR performs well both with bulk sequencing data and with single cell data. In addition, we show that the weights returned by SwarmTCR are biologically interpretable. CONCLUSIONS: Computationally predicting the specificity of T cell receptors can be a powerful tool to shed light on the immune response against infectious diseases and cancers, autoimmunity, cancer immunotherapy, and immunopathology. SwarmTCR is distributed freely under the terms of the GPL-3 license. The source code and all sequencing data are available at GitHub ( https://github.com/thecodingdoc/SwarmTCR ).


Asunto(s)
Receptores de Antígenos de Linfocitos T , Programas Informáticos , Análisis por Conglomerados , Biología Computacional , Inmunoterapia , Receptores de Antígenos de Linfocitos T/genética
9.
Urologiia ; (4): 25-29, 2021 Sep.
Artículo en Ruso | MEDLINE | ID: mdl-34486271

RESUMEN

INTRODUCTION: Damage to the structure of the kidney in blunt trauma leads to disruption of angioarchitectonics and microcirculation. OBJECTIVE: to establish the dependence of renal function and circulatory system on the severity of injury and the type of blunt renal trauma. MATERIALS AND METHODS: The clinical and laboratory homeostasis tests were carried out in 127 patients with the kidney parenchyma contusion and ruptures in the nearest posttraumatic period. RESULTS: Five factors and five clusters of signs were revealed. Tissue level reactions predominate in case of contusion injury of less than half of the organ. Trauma of more than half of the kidney and parenchyma rupture involve the circulatory system in the response reaction. CONCLUSION: the volume/area and type of damage are predictors in the level of the functional response of the organism - organ or organismal.


Asunto(s)
Heridas no Penetrantes , Análisis por Conglomerados , Homeostasis , Humanos , Riñón/lesiones , Riñón/fisiología , Estudios Retrospectivos , Heridas no Penetrantes/complicaciones
10.
Molecules ; 26(16)2021 Aug 19.
Artículo en Inglés | MEDLINE | ID: mdl-34443624

RESUMEN

Peptide synthesis is an area with a wide field of application, from biomedicine to nanotechnology, that offers the option of simultaneously synthesizing a large number of sequences for the purpose of preliminary screening, which is a powerful tool. Nevertheless, standard protocols generate large volumes of solvent waste. Here, we present a protocol for the multiple Fmoc solid-phase peptide synthesis in tea bags, where reagent recycling steps are included. Fifty-two peptides with wide amino acid composition and seven to twenty amino acid residues in length were synthesized in less than three weeks. A clustering analysis was performed, grouping the peptides by physicochemical features. Although a relationship between the overall yield and the physicochemical features of the sequences was not established, the process showed good performance despite sequence diversity. The recycling system allowed to reduce N, N-dimethylformamide usage by 25-30% and reduce the deprotection reagent usage by 50%. This protocol has been optimized for the simultaneous synthesis of a large number of peptide sequences. Additionally, a reagent recycling system was included in the procedure, which turns the process into a framework of circular economy, without affecting the quality of the products obtained.


Asunto(s)
Reciclaje/economía , Técnicas de Síntesis en Fase Sólida/economía , Técnicas de Síntesis en Fase Sólida/métodos , Té/química , Fenómenos Químicos , Análisis por Conglomerados
11.
BMC Public Health ; 21(1): 1597, 2021 08 30.
Artículo en Inglés | MEDLINE | ID: mdl-34461855

RESUMEN

BACKGROUND: Little comprehensive information on overall epidemic trend of notifiable respiratory infectious diseases is available in Shandong Province, China. This study aimed to determine the spatiotemporal distribution and epidemic characteristics of notifiable respiratory infectious diseases. METHODS: Time series was firstly performed to describe the temporal distribution feature of notifiable respiratory infectious diseases during 2005-2014 in Shandong Province. GIS Natural Breaks (Jenks) was applied to divide the average annual incidence of notifiable respiratory infectious diseases into five grades. Spatial empirical Bayesian smoothed risk maps and excess risk maps were further used to investigate spatial patterns of notifiable respiratory infectious diseases. Global and local Moran's I statistics were used to measure the spatial autocorrelation. Spatial-temporal scanning was used to detect spatiotemporal clusters and identify high-risk locations. RESULTS: A total of 537,506 cases of notifiable respiratory infectious diseases were reported in Shandong Province during 2005-2014. The morbidity of notifiable respiratory infectious diseases had obvious seasonality with high morbidity in winter and spring. Local Moran's I analysis showed that there were 5, 23, 24, 4, 20, 8, 14, 10 and 7 high-risk counties determined for influenza A (H1N1), measles, tuberculosis, meningococcal meningitis, pertussis, scarlet fever, influenza, mumps and rubella, respectively. The spatial-temporal clustering analysis determined that the most likely cluster of influenza A (H1N1), measles, tuberculosis, meningococcal meningitis, pertussis, scarlet fever, influenza, mumps and rubella included 74, 66, 58, 56, 22, 64, 2, 75 and 56 counties, and the time frame was November 2009, March 2008, January 2007, February 2005, July 2007, December 2011, November 2009, June 2012 and May 2005, respectively. CONCLUSIONS: There were obvious spatiotemporal clusters of notifiable respiratory infectious diseases in Shandong during 2005-2014. More attention should be paid to the epidemiological and spatiotemporal characteristics of notifiable respiratory infectious diseases to establish new strategies for its control.


Asunto(s)
Enfermedades Transmisibles , Subtipo H1N1 del Virus de la Influenza A , Teorema de Bayes , China/epidemiología , Análisis por Conglomerados , Humanos , Incidencia , Análisis Espacio-Temporal
12.
Comput Methods Programs Biomed ; 209: 106332, 2021 Sep.
Artículo en Inglés | MEDLINE | ID: mdl-34365313

RESUMEN

BACKGROUND AND OBJECTIVE: Pulmonary nodules have different shapes and uneven density, and some nodules adhere to blood vessels, pleura and other anatomical structures, which increase the difficulty of nodule segmentation. The purpose of this paper is to use multiscale residual U-Net to accurately segment lung nodules with complex geometric shapes, while comparing it with fuzzy C-means clustering and manual segmentation. METHOD: We selected 58 computed tomography (CT) scan images of patients with different lung nodules for image segmentation. This paper proposes an automatic segmentation algorithm for lung nodules based on multiscale residual U-Net. In order to verify the accuracy of the method, we also conducted comparative experiments, while comparing it with fuzzy C-means clustering. RESULTS: Compared with the other two methods, the segmentation of lung nodules based on multiscale residual U-Net has a higher accuracy, with an accuracy rate of 94.57%. This method not only maintains a high accuracy rate, but also shortens the recognition time significantly with a segmentation time of 3.15 s. CONCLUSIONS: The diagnosis method of lung nodules combined with deep learning has a good market prospect and can improve the efficiency of doctors in diagnosing benign and malignant lung nodules.


Asunto(s)
Algoritmos , Tomografía Computarizada por Rayos X , Análisis por Conglomerados , Progresión de la Enfermedad , Humanos , Procesamiento de Imagen Asistido por Computador
13.
Comput Intell Neurosci ; 2021: 9952596, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-34381500

RESUMEN

Active learning is aimed to sample the most informative data from the unlabeled pool, and diverse clustering methods have been applied to it. However, the distance-based clustering methods usually cannot perform well in high dimensions and even begin to fail. In this paper, we propose a new active learning method combined with variational autoencoder (VAE) and density-based spatial clustering of applications with noise (DBSCAN). It overcomes the difficulty of distance representation in high dimensions and prevents the distance concentration phenomenon from occurring in the computational learning literature with respect to high-dimensional p-norms. Finally, we compare our method with four common active learning methods and two other clustering algorithms combined with VAE on three datasets. The results demonstrate that our approach achieves competitive performance, and it is a new batch mode active learning algorithm designed for neural networks with a relatively small query batch size.


Asunto(s)
Redes Neurales de la Computación , Aprendizaje Basado en Problemas , Algoritmos , Análisis por Conglomerados
14.
Chaos ; 31(7): 073142, 2021 Jul.
Artículo en Inglés | MEDLINE | ID: mdl-34340330

RESUMEN

Coupled hair cells of the auditory and vestibular systems perform the crucial task of converting the energy of sound waves and ground-borne vibrations into ionic currents. We mechanically couple groups of living, active hair cells with artificial membranes, thus mimicking in vitro the coupled dynamical system. We identify chimera states and frequency clustering in the dynamics of these coupled nonlinear, autonomous oscillators. We find that these dynamical states can be reproduced by our numerical model with heterogeneity of the parameters. Furthermore, we find that this model is most sensitive to external signals when poised at the onset of synchronization, where chimera and cluster states are likely to form. We, therefore, propose that the partial synchronization in our experimental system is a manifestation of a system poised at the verge of synchronization with optimal sensitivity.


Asunto(s)
Quimera , Análisis por Conglomerados
15.
BMC Med Inform Decis Mak ; 21(1): 245, 2021 08 21.
Artículo en Inglés | MEDLINE | ID: mdl-34419027

RESUMEN

BACKGROUND: To enhance teleconsultation management, demands can be classified into different patterns, and the service of each pattern demand can be improved. METHODS: For the effective teleconsultation classification, a novel ensemble hierarchical clustering method is proposed in this study. In the proposed method, individual clustering results are first obtained by different hierarchical clustering methods, and then ensembled by one-hot encoding, the calculation and division of cosine similarity, and network graph representation. In the built network graph about the high cosine similarity, the connected demand series can be categorized into one pattern. For verification, 43 teleconsultation demand series are used as sample data, and the efficiency and quality of teleconsultation services are respectively analyzed before and after the demand classification. RESULTS: The teleconsultation demands are classified into three categories, erratic, lumpy, and slow. Under the fixed strategies, the service analysis after demand classification reveals the deficiencies of teleconsultation services, but analysis before demand classification can't. CONCLUSION: The proposed ensemble hierarchical clustering method can effectively category teleconsultation demands, and the effective demand categorization can enhance teleconsultation management.


Asunto(s)
Consulta Remota , Análisis por Conglomerados , Humanos
16.
BMJ ; 374: n1857, 2021 08 13.
Artículo en Inglés | MEDLINE | ID: mdl-34389547

RESUMEN

OBJECTIVE: To determine whether the addition of placental growth factor (PlGF) measurement to current clinical assessment of women with suspected pre-eclampsia before 37 weeks' gestation would reduce maternal morbidity without increasing neonatal morbidity. DESIGN: Stepped wedge cluster randomised control trial from 29 June 2017 to 26 April 2019. SETTING: National multisite trial in seven maternity hospitals throughout the island of Ireland PARTICIPANTS: Women with a singleton pregnancy between 20+0 to 36+6 weeks' gestation, with signs or symptoms suggestive of evolving pre-eclampsia. Of the 5718 women screened, 2583 were eligible and 2313 elected to participate. INTERVENTION: Participants were assigned randomly to either usual care or to usual care plus the addition of point-of-care PlGF testing based on the randomisation status of their maternity hospital at the time point of enrolment. MAIN OUTCOMES MEASURES: Co-primary outcomes of composite maternal morbidity and composite neonatal morbidity. Analysis was on an individual participant level using mixed-effects Poisson regression adjusted for time effects (with robust standard errors) by intention-to-treat. RESULTS: Of the 4000 anticipated recruitment target, 2313 eligible participants (57%) were enrolled, of whom 2219 (96%) were included in the primary analysis. Of these, 1202 (54%) participants were assigned to the usual care group, and 1017 (46%) were assigned the intervention of additional point-of-care PlGF testing. The results demonstrate that the integration of point-of-care PlGF testing resulted in no evidence of a difference in maternal morbidity-457/1202 (38%) of women in the control group versus 330/1017 (32%) of women in the intervention group (adjusted risk ratio (RR) 1.01 (95% CI 0.76 to 1.36), P=0.92)-or in neonatal morbidity-527/1202 (43%) of neonates in the control group versus 484/1017 (47%) in the intervention group (adjusted RR 1.03 (0.89 to 1.21), P=0.67). CONCLUSIONS: This was a pragmatic evaluation of an interventional diagnostic test, conducted nationally across multiple sites. These results do not support the incorporation of PlGF testing into routine clinical investigations for women presenting with suspected preterm pre-eclampsia, but nor do they exclude its potential benefit. TRIAL REGISTRATION: ClinicalTrials.gov NCT02881073.


Asunto(s)
Mortalidad Materna/tendencias , Factor de Crecimiento Placentario/metabolismo , Pruebas en el Punto de Atención/normas , Preeclampsia/diagnóstico , Adulto , Biomarcadores/sangre , Estudios de Casos y Controles , Análisis por Conglomerados , Femenino , Edad Gestacional , Humanos , Lactante , Mortalidad Infantil/tendencias , Recién Nacido , Irlanda , Evaluación de Resultado en la Atención de Salud , Factor de Crecimiento Placentario/sangre , Pruebas en el Punto de Atención/estadística & datos numéricos , Preeclampsia/sangre , Preeclampsia/etnología , Embarazo
17.
Artículo en Inglés | MEDLINE | ID: mdl-34444179

RESUMEN

Whether high blood eosinophil counts may define a better phenotype in bronchiectasis patients, as shown in chronic obstructive pulmonary disease (COPD), remains to be investigated. Differential phenotypic characteristics according to eosinophil counts were assessed using a biostatistical approach in a large cohort study from the Spanish Online Bronchiectasis Registry (RIBRON). The 906 patients who met the inclusion criteria were clustered into two groups on the basis of their eosinophil levels. The potential differences according to the bronchiectasis severity index (BSI) score between two groups (Mann-Whitney U test and eosinophil count threshold: 100 cells/µL) showed the most balanced cluster sizes: above-threshold and below-threshold groups. Patients above the threshold exhibited significantly better clinical outcomes, lung function, and nutritional status, while showing lower systemic inflammation levels. The proportion of patients with mild disease was higher in the above-threshold group, while the below-threshold patients were more severe. Two distinct clinical phenotypes of stable patients with non-cystic fibrosis (CF) bronchiectasis of a wide range of disease severity were established on the basis of blood eosinophil counts using a biostatistical approach. Patients classified within the above-threshold cluster were those exhibiting a mild disease, significantly better clinical outcomes, lung function, and nutritional status while showing lower systemic inflammatory levels. These results will contribute to better characterizing bronchiectasis patients into phenotypic profiles with their clinical implications.


Asunto(s)
Bronquiectasia , Enfermedad Pulmonar Obstructiva Crónica , Análisis por Conglomerados , Estudios de Cohortes , Eosinófilos , Humanos , Fenotipo , Índice de Severidad de la Enfermedad
18.
Pan Afr Med J ; 38: 401, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-34381545

RESUMEN

Introduction: falls contribute to almost one-fifth of injury-related deaths. The majority of these occur in low- and middle-income countries. The impact of fall injury in low- and middle-income countries is greater in younger individuals. We aimed to determine the epidemiology of falls among rural Ghanaian children. Methods: from March to May, 2018, we conducted a cluster-randomized household survey of caregivers in a rural Ghanaian sub-district, regarding household child falls and their severity. We utilized a previously validated survey tool for household child injury. Associations between household child falls and previously described predictors of household child injury were examined with multivariable logistic regression. These included age and gender of the child, household socioeconomic status, caregiver education, employment status, and their beliefs on why household child injuries occur. Results: three hundred and fifty-seven caregivers of 1,016 children were surveyed. One hundred and sixty-four children under 18 years had sustained a household fall within the past six months, giving a household child fall prevalence of 16% (95% C.I, 14%-19%). Mean age was 4.4 years; 59% were males. Ground level falls were more common (80%). Severity was mostly moderate (86%). Most caregivers believed household child injuries occurred due to lack of supervision (85%) or unsafe environment (75%); only 2% believed it occurred because of fate. Girls had reduced odds of household falls (adjusted O.R 0.6; 95% C.I 0.4-0.9). Five to nine year-old and 15-17 year-old children had reduced odds of household falls (adjusted O.R 0.4; 95% C.I 0.2-0.7 and 0.1; 95% C.I 0.02-0.3, respectively) compared to 1-4 year-olds. Caregiver engagement in non-salary paying work was associated with increased odds of household child falls (adjusted O.R 2.2; 95% C.I 1.0-4.7) compared to unemployed caregivers. There was no association between household child falls and caregiver education, socioeconomic status and beliefs about why household child injuries occurred. Conclusion: the prevalence of household child falls in rural Ghana was 16%. This study confirms the need to improve supervision of all children to reduce household falls, especially younger children and particularly boys. Majority of caregivers also acknowledge the role of improper child supervision and unsafe environments in household child falls. These beliefs should be reinforced and emphasized in campaigns to prevent household child falls in rural communities.


Asunto(s)
Accidentes por Caídas/estadística & datos numéricos , Cuidadores/estadística & datos numéricos , Adolescente , Adulto , Anciano , Anciano de 80 o más Años , Niño , Preescolar , Análisis por Conglomerados , Escolaridad , Empleo/estadística & datos numéricos , Femenino , Ghana/epidemiología , Humanos , Lactante , Masculino , Persona de Mediana Edad , Prevalencia , Factores de Riesgo , Factores Sexuales , Factores Socioeconómicos , Encuestas y Cuestionarios , Adulto Joven
19.
J Chem Phys ; 155(5): 054102, 2021 Aug 07.
Artículo en Inglés | MEDLINE | ID: mdl-34364321

RESUMEN

Markov state models (MSMs) have become one of the preferred methods for the analysis and interpretation of molecular dynamics (MD) simulations of conformational transitions in biopolymers. While there is great variation in terms of implementation, a well-defined workflow involving multiple steps is often adopted. Typically, molecular coordinates are first subjected to dimensionality reduction and then clustered into small "microstates," which are subsequently lumped into "macrostates" using the information from the slowest eigenmodes. However, the microstate dynamics is often non-Markovian, and long lag times are required to converge the relevant slow dynamics in the MSM. Here, we propose a variation on this typical workflow, taking advantage of hierarchical density-based clustering. When applied to simulation data, this type of clustering separates high population regions of conformational space from others that are rarely visited. In this way, density-based clustering naturally implements assignment of the data based on transitions between metastable states, resulting in a core-set MSM. As a result, the state definition becomes more consistent with the assumption of Markovianity, and the timescales of the slow dynamics of the system are recovered more effectively. We present results of this simplified workflow for a model potential and MD simulations of the alanine dipeptide and the FiP35 WW domain.


Asunto(s)
Dipéptidos/química , Cadenas de Markov , Simulación de Dinámica Molecular/estadística & datos numéricos , Proteínas/química , Análisis por Conglomerados , Conformación Proteica , Dominios WW
20.
Accid Anal Prev ; 160: 106320, 2021 Sep.
Artículo en Inglés | MEDLINE | ID: mdl-34358751

RESUMEN

Crash safety of electric two-wheelers (ETWs) has been one of the most important safety issues in China due to their high proportion of involvement in traffic accidents. Automated Emergency Braking (AEB) systems have proven to be effective in reducing the number of fatalities and injuries in traffic accidents. Providing test scenarios is one of the fundamental tasks required for establishing a set of AEB test programs for ETWs. Compared to traditional in-depth accident data, accident data accompanied with video recordings provide more accurate accident information prior to a crash as both the traffic environment and the crash process can be observed from the video. In this study, a set of typical AEB test scenarios for ETWs was developed using accident data with video information. Video recordings of 630 car-to-ETW crashes in China from 2010 to 2021 were selected from the VRU Traffic Accident database with Video (VRU-TRAVi). A K-medoids1 cluster analysis was carried out based on variables including the collision time, visual obstruction, motion of the car and ETW before the collision, relative motion direction between the car and ETW, and the ETW type. The velocity information of cars and ETWs was also accounted for in each clustering scenario. Seven typical pre-crash scenarios were obtained, including five electric-scooter (E-scooter) scenarios (representing two scenarios where the ETWs are approaching the car from the left side, two scenarios where the ETWs are approaching the car in the same direction and another scenario where the ETWs are approaching the car in the opposite direction) and two electric-bike (E-bike) scenarios where the E-bikes are approaching the car in the perpendicular direction. Both E-bike scenarios are consistent with the E-scooter scenario except for the ETW type and velocity range; therefore, by combining the E-bike and E-scooter scenarios, five ETW scenarios were finally recommended as AEB test scenarios. By comparing with typical scenarios extracted based on the China In-Depth Accident Study (CIDAS) data and the China New Car Assessment Program (C-NCAP) test scenarios, the results show that future AEB test scenarios for ETWs should focus on scenarios with visual obstructions and scenarios where either the car or the ETW is turning, with a velocity range of 15-30 km/h for ETWs.


Asunto(s)
Accidentes de Tránsito , Equipos de Seguridad , Accidentes de Tránsito/prevención & control , Automóviles , Análisis por Conglomerados , Humanos , Grabación en Video
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