bluuebunny/crossref_metadata_2025 huggingface dataset:
The Academic Development Trajectories of the Lean Production Based on Main Path Analysis Method
Authors: Lin Pi-Yu , Chen Kai-Ying , Cheng Chen-Yang , Su Wei-Hao , Lu Louis Y. Y.
Published: August 2022

Enterprises looking to be competitive are constantly looking for a continuous increase in productivity, quality, and level of services. With the development of the industry 4.0 concept, manufacturers are more confident about the new advantages of automation and systems integration. Lean management is a well-developed and empirically proven managerial strategy. Combining lean and industry 4.0 practices seems to be a necessary evolutionary step to further raise the level of operational excellence. This study applied the main path analysis method to explore the development trend of lean management in the academic field. First, this study adopted the Scopus database to collect relevant papers, then analyzed their overall development trajectory by using Main Path 437 software, and used the g-index and h-index to identify more influential journals. Next, this study clustered the papers with similar topics into several groups, and then used Wordle software to present the keywords of each group in a word cloud that serves as a reference for naming. Thus, the top five groups obtained are as follows: “Lean production concept and application”, “Lean Six Sigma concept and application”, “Lean system integration and application”, “Lean construction concept and application”, and “Lean healthcare concept and application”. Finally, this study provides explanations and conclusions on each group’s development trajectory, as well as research recommendations in the field of lean production. The findings can serve as guides for industry, government, and academia as they develop future lean production development strategies. This study utilized an integrated analysis approach to successfully and effectively depict the trajectory of lean production development and applications, identify future research and development directions, and generate technological forecasts.
Theory of Microwave Remote Sensing of Vegetation Effects, SoOp and Rough Soil Surface Backscattering
Authors: Tsang Leung , Liao Tien-Hao , Gao Ruoxing , Xu Haokui , Gu Weihui , Zhu Jiyue
Published: August 2022

In this paper, we provide updates on our recent work on the theory of microwave remote sensing for applications in remote sensing of soil moisture and snow water equivalent (SWE). The three topics are the following. (i) For the effects of forests and vegetation, we developed the hybrid method of NMM3D full-wave simulations over the vegetation field and forest canopies. In the hybrid method, we combined the use of commercial off-the-shelf software and wave multiple scattering theory (W-MST). The results showed much larger transmission than classical radiative transfer theory. (ii) In signals of opportunity at L-band and P-band, which are radar bistatic scattering in the vicinity of the specular direction, we developed the Analytical Kirchhoff solution (AKS) and Numerical Kirchhoff approach (NKA) in the calculations of coherent waves and incoherent waves. We also took into account of the effects of topographical elevations and slopes which have strong influences. (iii) In rough surface radar backscattering, we used the volume integral equation approach for NMM3D full-wave simulations for soil surfaces with kh up to 15. The simulations were calculated for the X-band and Ku-band and the results showed saturation effects. The simulation results can be applied to microwave remote sensing of SWE at these two frequencies.
An Approach for Retrieving Consistent Time Series “Urban Core–Suburban-Rural” (USR) Structure Using Nighttime Light Data from DMSP/OLS and NPP/VIIRS
Authors: Huang Yaohuan , Yang Jie , Chen Mingxing , Wu Chengbin , Ren Hongyan , Liu Yesen
Published: August 2022

The long time series and consistent “urban core-suburban-rural” (USR) structure in a city region is essential to understanding urban–suburban–rural interaction and urbanization pathways. It is always considered to be a single land use type (e.g., impervious area) in remote sensing research. The long-term (1992–present) nighttime light (NTL) data of the Defense Meteorological Satellite Program-Operational Linescan System (DMSP-OLS) and the Suomi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) provide the potential for retrieving time series of USR structure. In this study, we propose an improved approach to mapping the USR structure of the three subcategories based on a heuristic algorithm of Mann–Kendall mutation detection on the NTL quantile curve. First, a minor adjustment of VIIRS NTL is applied for matching the value ranges of DMSP NTL data and keeping the advantage of VIIRS to generate a long-term NTL dataset. Second, the heuristic algorithm of Mann–Kendall mutation detection is processed to find two optimal thresholds in the NTL quantile curve, which is used for USR extraction. Finally, a temporal consistency check is used to post-process the initial USR area for obtaining a more consistent and reliable USR sequence. To evaluate the performance of the proposed method, we retrieved the USR structures of 19 typical cities in China from 1992 to 2020 based on NTL datasets. The evaluations of spatiotemporal consistency compared with the validation data indicate that the USR retrieval results show good agreement with the land use map derived from Landsat images and the time series product from MODIS. The average overall accuracy (OA) of overall urban extent is higher than 0.95 and the average kappa coefficient (KC) reaches 0.6. Moreover, we investigated the urban dynamics and USR interactions of 19 cities from 1992 to 2020. Overall, this study proposes an improved approach for long-term USR mapping from NTL images at a regional scale and it will provide a valuable method for urbanization dynamics analysis.
Dual-Branch-AttentionNet: A Novel Deep-Learning-Based Spatial-Spectral Attention Methodology for Hyperspectral Data Analysis
Authors: Praveen Bishwas , Menon Vineetha
Published: August 2022

Recently, deep learning-based classification approaches have made great progress and now dominate a wide range of applications, thanks to their Herculean discriminative feature learning ability. Despite their success, for hyperspectral data analysis, these deep learning based techniques tend to suffer computationally as the magnitude of the data soars. This is mainly because the hyperspectral imagery (HSI) data are multidimensional, as well as giving equal importance to the large amount of temporal and spatial information in the HSI data, despite the redundancy of information in the temporal and spatial domains. Consequently, in literature, this equal information emphasis has proven to affect the classification efficacy negatively in addition to increasing the computational time. As a result, this paper proposes a novel dual branch spatial-spectral attention based classification methodology that is computationally cheap and capable of selectively accentuating cardinal spatial and spectral features while suppressing less useful ones. The theory of feature extraction with 3D-convolutions alongside a gated mechanism for feature weighting using bi-directional long short-term memory is used as a spectral attention mechanism in this architecture. In addition, a union of 3D convolutional neural network (3D-CNN) and a residual network oriented spatial window-based attention mechanism is proposed in this work. To validate the efficacy of our proposed technique, the features collected from these spatial and spectral attention pipelines are transferred to a feed-forward neural network (FNN) for supervised pixel-wise classification of HSI data. The suggested spatial-spectral attention based hyperspectral data analysis and image classification methodology outperform other spatial-only, spectral-only, and spatial-spectral feature extraction based hyperspectral image classification methodologies when compared, according to experimental results.
The Spatiotemporal Changes in Ecological–Environmental Quality Caused by Farmland Consolidation Using Google Earth Engine: A Case Study from Liaoning Province in China
Authors: Zhang Maoxin , He Tingting , Wu Cifang , Li Guangyu
Published: August 2022

Farmland consolidation (FC) is among the measures to solve farmland issues, such as farmland fragmentation, and its impact on the ecological environment has always been controversial. In terms of long-term series and large-area analysis, the calculation of a large amount of data makes the analysis of the ecological–environmental quality of farmland consolidation very difficult. To solve this problem, our study applied a remote sensing ecological index model on the Google Earth Engine platform to analyze the changes in the ecological–environmental quality in two prefecture-level cities in Liaoning Province over the past 20 years. In addition, we analyzed the impacts of FC projects on the ecological environment from 2006 to 2018 and compared them to farmland without consolidation. The study results show that FC caused negative impacts on the quality of the ecological environment during the FC period (2006–2018) and that the FC’s positive effects take time to develop. In each FC phase, the results showed that FC exhibited negative effects before 2010 because the proportion of ecological–environmental quality reductions (0–47.67%) was higher than the proportion of increases (9.62–46.15%) in those FC phases. Since 2011, the area experiencing positive ecological–environmental benefits (31.96–72.01%) enabled by FC is higher than the area of negative impact (2.24–18.07%). This seems to be triggered by policy evolution. Based on the trend analysis, the proportion of FC areas with improved ecological–environmental quality grew faster (Gini index decreased 0.09) than that of farmland without consolidation (Gini index decreased 0.05) from before FC to after FC. Moreover, the new FC projects (2011–2018) performed better than the early projects (2006–2010), which may be due to policy evolution and technological advancements. However, the new FC projects (2011–2018) caused a dramatic decrease in ecological–environmental quality in a small number of areas due to the study time constraints. In conclusion, we believe that FC could improve the ecological–environmental quality of farmland, whereas some measures are needed to reduce its temporal negative impact on ecological–environmental quality, which may be caused by human interference. The remote sensing ecological index obtained using the Google Earth Engine platform provided an effective and reliable method for detecting the impacts of FC on the ecological–environmental quality of farmland. This could provide the basis and support for the monitoring of ecological–environmental changes in FC areas at a regional level.
A Multi-Parametric and Multi-Layer Study to Investigate the Largest 2022 Hunga Tonga–Hunga Ha’apai Eruptions
Authors: D’Arcangelo Serena , Bonforte Alessandro , De Santis Angelo , Maugeri Salvatore Roberto , Perrone Loredana , Soldani Maurizio , Arena Giovanni , Brogi Federico , Calcara Massimo , Campuzano Saioa A. , Cianchini Gianfranco , Del Corpo Alfredo , Di Mauro Domenico , Fidani Cristiano , Ippolito Alessandro , Lepidi Stefania , Marchetti Dedalo , Nardi Adriano , Orlando Martina , Piscini Alessandro , Regi Mauro , Sabbagh Dario , Zhima Zeren , Yan Rui
Published: August 2022

On 20 December 2021, after six quiet years, the Hunga Tonga–Hunga Ha’apai volcano erupted abruptly. Then, on 15 January 2022, the largest eruption produced a plume well registered from satellites and destroyed the volcanic cone previously formed in 2015, connecting the two islands. We applied a multi-parametric and multi-layer study to investigate all the possible pre-eruption signals and effects of this volcanic activity in the lithosphere, atmosphere, and ionosphere. We focused our attention on: (a) seismological features considering the eruption in terms of an earthquake with equivalent energy released in the lithosphere; (b) atmospheric parameters, such as skin and air temperature, outgoing longwave radiation (OLR), cloud cover, relative humidity from climatological datasets; (c) varying magnetic field and electron density observed by ground magnetometers and satellites, even if the event was in the recovery phase of an intense geomagnetic storm. We found different precursors of this unique event in the lithosphere, as well as the effects due to the propagation of acoustic gravity and pressure waves and magnetic and electromagnetic coupling in the form of signals detected by ground stations and satellite data. All these parameters and their detailed investigation confirm the lithosphere–atmosphere–ionosphere coupling (LAIC) models introduced for natural hazards such as volcano eruptions and earthquakes.
High-Precision Population Spatialization in Metropolises Based on Ensemble Learning: A Case Study of Beijing, China
Authors: Bao Wenxuan , Gong Adu , Zhao Yiran , Chen Shuaiqiang , Ba Wanru , He Yuan
Published: August 2022

Accurate spatial population distribution information, especially for metropolises, is of significant value and is fundamental to many application areas such as public health, urban development planning and disaster assessment management. Random forest is the most widely used model in population spatialization studies. However, a reliable model for accurately mapping the spatial distribution of metropolitan populations is still lacking due to the inherent limitations of the random forest model and the complexity of the population spatialization problem. In this study, we integrate gradient boosting decision tree (GBDT), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM) and support vector regression (SVR) through ensemble learning algorithm stacking to construct a novel population spatialization model we name GXLS-Stacking. We integrate socioeconomic data that enhance the characterization of the population’s spatial distribution (e.g., point-of-interest data, building outline data with height, artificial impervious surface data, etc.) and natural environmental data with a combination of census data to train the model to generate a high-precision gridded population density map with a 100 m spatial resolution for Beijing in 2020. Finally, the generated gridded population density map is validated at the pixel level using the highest resolution validation data (i.e., community household registration data) in the current study. The results show that the GXLS-Stacking model can predict the population’s spatial distribution with high precision (R2 = 0.8004, MAE = 34.67 persons/hectare, RMSE = 54.92 persons/hectare), and its overall performance is not only better than the four individual models but also better than the random forest model. Compared to the natural environmental features, a city’s socioeconomic features are more capable in characterizing the spatial distribution of the population and the intensity of human activities. In addition, the gridded population density map obtained by the GXLS-Stacking model can provide highly accurate information on the population’s spatial distribution and can be used to analyze the spatial patterns of metropolitan population density. Moreover, the GXLS-Stacking model has the ability to be generalized to metropolises with comprehensive and high-quality data, whether in China or in other countries. Furthermore, for small and medium-sized cities, our modeling process can still provide an effective reference for their population spatialization methods.
Deformation Monitoring of Tailings Reservoir Based on Polarimetric Time Series InSAR: Example of Kafang Tailings Reservoir, China
Authors: Wu Hao , Zheng Xiangyuan , Fan Hongdong , Tian Zeming
Published: August 2022

Safe operation of tailings reservoirs is essential to protect downstream life and property, but current monitoring methods are inadequate in scale and refinement, and most reservoirs are built in low coherence areas far from cities. Use of polarization data to monitor deformation may improve area coherence and thus point selection density. With the example of the Kafang tailings reservoir and dual-polarization Sentinel-1 data from 9 August 2020 to 24 May 2021, homogeneous points of different polarization channels were identified with the hypothesis test of the confidence interval method. Results were fused, and BEST, sub-optimum scattering mechanism (SOM), and equal scattering mechanism (ESM) methods were used to optimize phase quality of persistent scatterer (PS) and distributed scatterer (DS) pixels and obtain more detailed deformation information on the area with time series processing. The fusion of homogeneous point sets obtained from different polarization intensity data increased the number of homogeneous points, which was 3.86% and 8.45% higher than that of VH and VV polarization images, respectively. The three polarization optimization methods improved point selection density. Compared with the VV polarization image, the high coherence point density increased by 1.83 (BEST), 3.66 (SOM), and 5.76 (ESM) times, whereas it increased by 1.17 (BEST), 1.84 (SOM), and 2.04 (ESM) times in the tailings reservoir. The consistency and reliability of different methods were good. By comparing the monitoring results of the three methods using polarization data, the hypothesis test of the confidence interval (HTCI) algorithm, and the polarization optimization method will effectively increase the point selection number of the study area, and the ESM method can show the deformation of tailings area more comprehensively. Monitoring indicated deformation of the tailings reservoir tended to diffuse outward from the area with the largest deformation and was relatively stable.
Global Mangrove Extent Change 1996–2020: Global Mangrove Watch Version 3.0
Authors: Bunting Pete , Rosenqvist Ake , Hilarides Lammert , Lucas Richard M. , Thomas Nathan , Tadono Takeo , Worthington Thomas A. , Spalding Mark , Murray Nicholas J. , Rebelo Lisa-Maria
Published: August 2022

Mangroves are a globally important ecosystem that provides a wide range of ecosystem system services, such as carbon capture and storage, coastal protection and fisheries enhancement. Mangroves have significantly reduced in global extent over the last 50 years, primarily as a result of deforestation caused by the expansion of agriculture and aquaculture in coastal environments. However, a limited number of studies have attempted to estimate changes in global mangrove extent, particularly into the 1990s, despite much of the loss in mangrove extent occurring pre-2000. This study has used L-band Synthetic Aperture Radar (SAR) global mosaic datasets from the Japan Aerospace Exploration Agency (JAXA) for 11 epochs from 1996 to 2020 to develop a long-term time-series of global mangrove extent and change. The study used a map-to-image approach to change detection where the baseline map (GMW v2.5) was updated using thresholding and a contextual mangrove change mask. This approach was applied between all image-date pairs producing 10 maps for each epoch, which were summarised to produce the global mangrove time-series. The resulting mangrove extent maps had an estimated accuracy of 87.4% (95th conf. int.: 86.2–88.6%), although the accuracies of the individual gain and loss change classes were lower at 58.1% (52.4–63.9%) and 60.6% (56.1–64.8%), respectively. Sources of error included misregistration in the SAR mosaic datasets, which could only be partially corrected for, but also confusion in fragmented areas of mangroves, such as around aquaculture ponds. Overall, 152,604 km2 (133,996–176,910) of mangroves were identified for 1996, with this decreasing by −5245 km2 (−13,587–1444) resulting in a total extent of 147,359 km2 (127,925–168,895) in 2020, and representing an estimated loss of 3.4% over the 24-year time period. The Global Mangrove Watch Version 3.0 represents the most comprehensive record of global mangrove change achieved to date and is expected to support a wide range of activities, including the ongoing monitoring of the global coastal environment, defining and assessments of progress toward conservation targets, protected area planning and risk assessments of mangrove ecosystems worldwide.
Fluid Migration through Permafrost and the Pool of Greenhouse Gases in Frozen Soils of an Oil and Gas Field
Authors: Kraev Gleb , Belonosov Andrei , Veremeeva Alexandra , Grabovskii Vasilii , Sheshukov Sergei , Shelokhov Ivan , Smirnov Alexander
Published: August 2022

Most methane (CH4) and carbon dioxide (CO2) emissions originate from the biodegradation of organic matter of soils and of degrading permafrost in the Arctic. However, there is limited evidence of the activity of geological sources, and little understanding of the pathways of migration of gaseous fluids through the porous mineral matrix filled with ice. We estimated the effect of geological factors on the winter storage of the greenhouse gases in frozen soils by statistical analysis of the geodatabase, which combined a field gas survey of frozen soils, subsurface sounding, and remote sensing data. Frozen soils stored on average 0.016 g CH4 m−3 and 11.5 g CO2 m−3. Microseeps, recognized by isolated anomalies of helium, had 30% higher CH4 concentrations. Lineaments marking margins of tectonic blocks were estimated to have 300% higher CH4 concentrations. High concentrations of propane and ethane indicated the contribution of diffuse fluid flow from hydrocarbon-bearing beds on 95% of the 130 km2 study area. In addition to the fluid contribution, we estimated an overwintering pool of greenhouse gases in frozen soil for the first time. Being at least 0.01–0.1% of the soil organic matter mass, these gaseous forms of carbon can be critical for the early-summer Arctic ecosystem functioning.
Satellite-Based Flood Mapping through Bayesian Inference from a Sentinel-1 SAR Datacube
Authors: Bauer-Marschallinger Bernhard , Cao Senmao , Tupas Mark Edwin , Roth Florian , Navacchi Claudio , Melzer Thomas , Freeman Vahid , Wagner Wolfgang
Published: August 2022

Spaceborne Synthetic Aperture Radar (SAR) are well-established systems for flood mapping, thanks to their high sensitivity towards water surfaces and their independence from daylight and cloud cover. Particularly able is the 2014-launched Copernicus Sentinel-1 C-band SAR mission, with its systematic monitoring schedule featuring global land coverage in a short revisit time and a 20 m ground resolution. Yet, variable environment conditions, low-contrasting land cover, and complex terrain pose major challenges to fully automated flood monitoring. To overcome these issues, and aiming for a robust classification, we formulate a datacube-based flood mapping algorithm that exploits the Sentinel-1 orbit repetition and a priori generated probability parameters for flood and non-flood conditions. A globally applicable flood signature is obtained from manually collected wind- and frost-free images. Through harmonic analysis of each pixel’s full time series, we derive a local seasonal non-flood signal comprising the expected backscatter values for each day-of-year. From those predefined probability distributions, we classify incoming Sentinel-1 images by simple Bayes inference, which is computationally slim and hence suitable for near-real-time operations, and also yields uncertainty values. The datacube-based masking of no-sensitivity resulting from impeding land cover and ill-posed SAR configuration enhances the classification robustness. We employed the algorithm on a 6-year Sentinel-1 datacube over Greece, where a major flood hit the region of Thessaly in 2018. In-depth analysis of model parameters and sensitivity, and the evaluation against microwave and optical reference flood maps, suggest excellent flood mapping skill, and very satisfying classification metrics with about 96% overall accuracy and only few false positives. The presented algorithm is part of the ensemble flood mapping product of the Global Flood Monitoring (GFM) component of the Copernicus Emergency Management Service (CEMS).
Assessing Macro Disease Index of Wheat Stripe Rust Based on Segformer with Complex Background in the Field
Authors: Deng Jie , Lv Xuan , Yang Lujia , Zhao Baoqiang , Zhou Congying , Yang Ziqian , Jiang Jiarui , Ning Ning , Zhang Jinyu , Shi Junzheng , Ma Zhanhong
Published: August 2022

Wheat stripe rust (WSR) is a foliar disease that causes destructive damage in the wheat production context. Accurately estimating the severity of WSR in the autumn growing stage can help to objectively monitor the disease incidence level of WSR and predict the nationwide disease incidence in the following year, which have great significance for controlling its nationwide spread and ensuring the safety of grain production. In this study, to address the low accuracy and the efficiency of disease index estimation by traditional methods, WSR-diseased areas are segmented based on Segformer, and the macro disease index (MDI) is automatically calculated for the measurement of canopy-scale disease incidence. The results obtained with different semantic segmentation algorithms, loss functions, and data sets are compared for the segmentation effect, in order to address the severe class imbalance in disease region segmentation. We find that: (1) The results of the various models differed significantly, with Segformer being the best algorithm for WSR segmentation (rust class F1 score = 72.60%), based on the original data set; (2) the imbalanced nature of the data has a significant impact on the identification of the minority class (i.e., the rust class), for which solutions based on loss functions and re-weighting of the minority class are ineffective; (3) data augmentation of the minority class or under-sampling of the original data set to increase the proportion of the rust class greatly improved the F1-score of the model (rust class F1 score = 86.6%), revealing that re-sampling is a simple and effective approach to alleviating the class imbalance problem. Finally, the MDI was used to evaluate the models based on the different data sets, where the model based on the augmented data set presented the best performance (R2 = 0.992, RMSE = 0.008). In conclusion, the deep-learning-based semantic segmentation method, and the corresponding optimization measures, applied in this study allow us to achieve pixel-level accurate segmentation of WSR regions on wheat leaves, thus enabling accurate assessment of the degree of WSR disease under complex backgrounds in the field, consequently providing technical support for field surveys and calculation of the disease level.
Aproximación al uso de los análisis en fresco del camarón como indicador predictivo de su crecimiento en cultivo
Authors: Varela Alexander
Published: August 2022

Se realizan análisis estadísticos sobre los resultados de 76 estanques de cultivo de camarones en Sonora, México. En ellos, se evalúa la correlación entre tres variables predictivas propuestas: Grado de condición de hepatopáncreas, Gregarinas y Epibiontes. Estableciendo al Incremento Semanal Promedio (ISP), como variable de respuesta. Se aplica un Análisis de componentes principales, en el cual se observa que estas variables presentaron correlaciones negativas con el ISP. Al realizar análisis de regresión lineal y ANOVA, no se detectan correlaciones a p<0,10 entre el Grado de hepatopáncreas y los niveles de epibiontes con el ISP, para los datos registrados y bajo las condiciones específicas analizadas. Por su parte, los datos de infestación de gregarinas y el ISP si presentan una correlación estadísticamente significativa con p <0,05, indicando que esta parasitosis provoca efectos negativos sobre el rendimiento de los cultivos, incluso en organismos que no están severamente infestados.
Using a Massive Open Online Course (MOOC) to promote infection prevention and control learning in healthcare education
Authors: Silén-Lipponen Marja , Koponen Leena , Korhonen Ulla , Myllymäki Mikko
Published: August 2022

Background: The prevention of healthcare-associated infections (HAIs) is one of the most important subjects in healthcare education. Aim: The aim of this study was to describe Finnish, Spanish, Portuguese, and Polish healthcare students’ perspectives on learning about HAIs using a Massive Open Online Course (MOOC). This study is part of the Erasmus+ project ‘Educating students for innovative infection prevention and control (IPC) practices in healthcare settings’ (InovSafeCare). Methods: The descriptive cross-sectional research design was used to describe healthcare students’ perspectives on learning about HAIs using the InovSafeCare MOOC (ISC-MOOC). The participants (N = 135) were students recruited from partner institutions. The project group developed a semi-structured questionnaire that was used for data collection, containing questions of technical and pedagogical usability. The data were analyzed by statistical methods and content analysis. Results: The ISC-MOOC facilitated healthcare students’ independent learning and promoted their knowledge of HAI prevention and control. Study materials were easy to use (84%), and the media of the study materials were of high standard (83%). Some technical problems (14%) were also identified with the use of the materials. The study materials were relevant (70%) for IPC learning but should also be provided in different languages. Conclusion: The MOOC will strengthen the role of the students as future healthcare professionals and will also be usable for those healthcare professionals who need to update their skills with today’s HAI requirements. MOOC should also be translated into other languages other than English.
Neurodidáctica, alternativa de innovación aplicada a estudiantes de educación superior, en el periodo del 2017-2021
Authors: Espinoza Rodríguez Jéssica Karol , Cisneros León Julio César , Valverde Pereira Angélica María
Published: August 2022

La neurodidáctica es la fusión de la neurociencia, la educación y la psicología, permite orientar la práctica docente vinculando las estrategias didácticas con los procesos neuronales, de tal forma, una revisión sistemática permitió evaluar el impacto del uso de la neurodidáctica como estrategia de aula para mejorar el proceso de formación de estudiantes universitarios. La metodología utilizada fue de alcance descriptivo – explicativo y enfoque cualitativo; en bases de datos como Scopus, Web of Science, Scielo, DOAJ y DIALNET, entre el periodo 2017 – 2021, incluyeron 60 artículos de revisión en idioma español, de diversos países de origen y seleccionados solo 10 artículos con aportes pertinentes a la neurodidáctica, procesos cognitivos y satisfacción emocional ante el aprendizaje. Concluyendo que las universidades necesitan incorporar alternativas de innovación en los procesos áulicos y la aplicación de la neurodidáctica puede contribuir al mejoramiento de la práctica docente y por ende al desarrollo del aprendizaje significativo.
Um minuto para a interdisciplinaridade: um retrato da Educação Ambiental em uma escola pública paulista
Authors: Tamborlin Jhonatan Fernandes , Valdanha Neto Diógenes , Platzer Maria Betanea
Published: August 2022

: Este artigo relata um estudo de caso que teve o objetivo principal de compreender a visão de docentes e discentes de uma escola pública estadual paulista sobre os vários processos de Educação Ambiental (EA) atuantes no dia a dia da escola, bem como os materiais didáticos e as metodologias empregadas pelos educadores. Foram utilizados questionários e entrevistas para o levantamento dos dados, totalizando a participação de 50 estudantes e 03 docentes dos anos finais do Ensino Fundamental. Os resultados revelam limites para a EA escolar na forma de projetos que se destacam do cotidiano e conteúdos de sala de aula. Os participantes indicam alternativas para a transformação desse cenário, com maior centralidade para a EA na escola.
Reflexões sobre Educação Ambiental e Ecossocialismo no Brasil pós-pandemia
Authors: Valle Luis Felipe
Published: August 2022

Agravados pela pandemia trazida pela Covid-19, problemas como fome, desemprego, miséria, desmatamento e poluição podem ser entendidos como sinais de uma necessária e urgente mudança nas bases pedagógicas do ensino brasileiro diante do potencial transformador da Educação Ambiental na construção de formas de desenvolvimento socioeconômico, cultural e de organização política mais alinhadas aos ciclos ecológicos e dinâmicas da natureza que, há séculos, vem sendo reduzida a matérias-primas e recursos para obtenção de lucros através do consumismo. A partir de uma revisão bibliográfica crítico-reflexiva, propõem-se novos olhares sobre como a Educação Ambiental pode trazer soluções aos problemas estruturais que afligem o Brasil, conduzindo a uma nova práxis engajada com a cidadania e a ecologia.
Rios urbanos: percebendo a importância por meio da Educação Ambiental
Authors: Braz Micaela Gomes , Duarte Ana Paula , Bottino Flávia
Published: August 2022

Ações que demonstrem a relação do indivíduo com o ambiente que o cerca assumem grande relevância para a sensibilização e a Educação Ambiental é uma ferramenta útil nesse processo. Uma ação educativa foi implementada a alunos dos níveis fundamental e médio em Passos (MG), a qual consistiu na apresentação de conceitos fundamentados nos problemas locais e aplicação de questionários. Verificamos que houve mudança na percepção da importância dos córregos urbanos após a ação educativa. A promoção de práticas ambientais no processo educativo colabora para a formação de indivíduos críticos e comprometidos com as questões ambientais.
Humanização dos animais de companhia: por uma Educação Ambiental animalitária
Authors: Fischer Marta Luciane , Carvalho Patricia Feiz Nardinelli Bernardes de , Carneiro Jaqueline Kliemke , Pimpão Claudia Turra
Published: August 2022

Objetivou-se caracterizar a relação da sociedade com os animais de companhia por meio de pesquisa quantitativa/transversal. A análise de 3863 participações demonstrou que apesar de cães e gatos serem os mais tutelados, cerca de 20%, especialmente jovens, tutelam animais silvestres nativos ou exóticos. A humanização dos pets foi analisada em 257 participações, cujas respostas foram agrupadas nos eixos: a partilha do espaço, o uso de produtos e serviços e a motivação para ampliação da tutela para animais não convencionais. A relação dos humanos com pets conclama um olhar mais cuidadoso, que encontra na sinergia entre a bioética e da educação ambiental, a possibilidade de transposição da perspectiva antropocêntrica/utilitarista para biocêntrica/ecocêntrica/abolicionista.
Aquaponia: um exemplo pioneiro de inclusão formal de Educação Ambiental no sistema educativo português
Authors: Martins Pedro
Published: August 2022

A Educação Ambiental (EA) em Portugal é abordada sobretudo de maneira informal. Este projeto pretendeu incluir formalmente um conceito relacionado com a EA no currículo de um curso profissional. O conceito escolhido foi a Aquaponia (criação em circuito fechado de peixes e de plantas) devido às características e valia técnica do mesmo. O projeto durou três anos, durante os quais se deu formação aos professores envolvidos. Realizaram-se inquéritos por questionário aos alunos e entrevistas aos professores, cuja análise de conteúdo permitiu solucionar alguns problemas iniciais.  Desta forma, atendeu-se à necessidade de dar respostas à crise ambiental global atuando localmente no currículo, enquanto mediador entre escola e sociedade.
Perfil de citocinas na patogênese da infecção do vírus Linfotrópico de células T humanas HTLV-1
Authors: Padilha Marcos Daniel Mendes , Viana Vitória Beatriz de Jesus , Balcazar Oscar David Albito , Balcázar Adriana Fernanda Albito , Albito Gabriela Anabel Aguilar , Costa Andreza Juliana Moreira da , Balcazar Maritza del Cisne Albito , Feitosa Rosimar Neris Martins
Published: August 2022

Introdução: Identificado em 1980 o HTLV-1 foi o primeiro retrovírus relacionado a neoplasias hematológicas em seres humanos, contribuindo para quadros severos de LTA, LLTA e PETMAH. As oncoproteínas do vírus HBZ e TAX levam a imunodesregulação e oncogênese de pacientes comprometidos. Objetivos: Elucidar o perfil de citocinas na patogênese do HTLV-1 e possíveis mecanismos para modelos imunoterapêuticos. Métodos: Se trata de uma revisão descritiva com análise sistemática, 102 artigos foram selecionados e apenas 54 incluídos, as palavras-chave foram padronizadas de acordo com o DeCS e os artigos categorizados para leitura na íntegra, utilizamos o fluxograma prisma para triagem e seleção dos artigos. Resultados e Discussão: Os altos níveis de IL-10 em pacientes LTA tem sido implicados na imunossupressão grave, CXCL9 e CXCL10 estão associadas ao aumento de células CD8⁺ e inflamação na medula espinhal, CCL3 afeta a inflamação do SNC através de macrófagos e astrócitos, a secreção de IFNγ contribui diretamente para o perfil de citocinas plasmáticas em PETMAH, a IL-6 induz a produção excessiva de VEGF, levando a angiogênese aumentada em tecidos sinoviais de artrite reumatóide relacionada ao HTLV-1. O TNFβ demonstrou promover a tumorigênese induzindo NF-kβ e IL-1β tem sido relacionada a inflamação crônica no SNC na PETMAH. Conclusão: O perfil imunopatológico imposto pelo HTLV-1 contribui para superexpressão de citocinas levando aos quadros de PETMAH e LTA. Citocinas IL-10, CXCL-9, CXCL-10, IFNs, IL-6 em combinação com adjuvantes podem estabelecer modelos eficazes para estudos em fase teste e contribuir com tratamentos terapêuticos futuros
Long-term outcomes of severe rheumatic mitral stenosis after undergoing percutaneous mitral commissurotomy and mitral valve replacement: A 10-year experience
Authors: Promratpan Wasinee , Theerasuwipakorn Nonthikorn , Lertsuwunseri Vorarit , Srimahachota Suphot
Published: August 2022

Introduction: Percutaneous mitral commissurotomy (PTMC) and mitral valve replacement (MVR) are treatments of choice for severe rheumatic mitral stenosis (MS). Data regarding the long-term outcomes of patients who underwent PTMC and MVR are limited. Methods: A retrospective cohort study was conducted to evaluate the long-term outcomes of patients with severe rheumatic MS who underwent PTMC or MVR between 2010 to 2020. The primary outcome comprised of all-cause death, stroke or systemic embolism, heart failure hospitalization and re-intervention. Cox regression was used to investigate predictors of the primary outcome. Results: 264 patients were included in analysis, 164 patients (62.1%) in PTMC group and 100 patients in MVR group (37.9%). The majority were females (80.7%) and had atrial fibrillation (68.6%). The mean age was 49.52 (SD: 13.03) years old. MVR group had more age and AF, higher Wilkins’ score with smaller MVA. Primary outcome occurred significantly higher in PTMC group (37.2% vs 22%, P=0.002), as well as, re-intervention (18.3% vs 0%, P<0.001). However, all-cause mortality, stroke or systemic embolism and heart failure hospitalization were not significantly different. In multivariate Cox regression analysis, PTMC (HR 1.94; 95%CI 1.14, 3.32; P=0.015), older age (HR 1.03; 95%CI 1.01, 1.06; P=0.009) and SPAP > 50 mmHg (HR 2.99; 95%CI 1.01, 8.84; P=0.047) were the only predictors of primary outcome. Conclusion: Primary outcome occurred in PTMC group more than MVR group which was driven by re-intervention. However, all-cause mortality, stroke or systemic embolism and heart failure hospitalization were not significantly different.
Trends in cardiac rehabilitation enrollment post-coronary artery bypass grafting upon implementation of automatic referral in Southeast Asia: A retrospective cohort study
Authors: Miralles-Resurreccion Karen V. , Grace Sherry L. , Cuenza Lucky R.
Published: August 2022

Introduction: Cardiac rehabilitation (CR) is an effective but underutilized intervention. Strategies have been identified to increase its use, but there is paucity of data testing them in low-resource settings. We sought to determine the effect of automatic referral post-coronary artery bypass graft (CABG) surgery on CR enrollment. Methods: This is a retrospective cohort study assessing cardiac patients referred to CR at a tertiary center in Southeast Asia from 2013 to 2019. The paper-based pathway was introduced at the end of 2012. The checklist with automatic CR referral on the third day post-operation prompted a nurse to educate the patient about CR, initiate phase 1 and encourage enrollment in phase 2. Patients who were not eligible for the pathway for administrative or clinical reasons were referred at the discretion of the attending physician (i.e., usual care). Enrollment was defined as attendance at≥1 CR visit. Results: Of 4792 patients referred during the study period, 394 enrolled in CR. Significantly more patients referred automatically enrolled compared to usual care (225 [11.8%] vs. 169 [5.8%]; OR=2.2, 95% CI=1.8-2.7), with increases up to 23.4% enrollment in 2014 (vs. average enrollment rate of 5.9% under usual referral). Patients who enrolled following automatic referral were significantly younger and more often employed (both P<0.001); no other differences were observed. Conclusion: In a lower-resource, Southeast Asian setting, automatic CR referral is associated with over two times greater enrollment in phase 2 CR, although efforts to maintain this effect are required.
Effects of curcumin and metformin on oxidative stress and apoptosis in heart tissue of type 1 diabetic rats
Authors: Naghdi Atefeh , Goodarzi Mohammad Taghi , Karimi Jamshid , Hashemnia Mohammad , Khodadadi Iraj
Published: August 2022

Introduction: Hyperglycemia enhances oxidative stress and apoptosis and induces damages in heart tissue. Based on antioxidant properties of curcumin and metformin, we hypothesized that these agents may exhibit cardioprotective effects by attenuating oxidative stress and modulating expression of the genes involved in apoptosis in type-1 diabetes. Methods: Thirty-six male rats were randomly divided into six groups; (N): control; (D): streptozotocin-induced diabetic rats; (D+Cur50) and (D+Cur150): diabetic rats treated with 50 and 150 milligram of curcumin per kilogram of body weight (mg/kg.bw), respectively; (D+Met300) and (D+Met500): diabetic rats received 300 and 500 mg/kg.bw of metformin, respectively. Heart tissues were dissected and gene expression levels of Bax, Bcl-2, and caspase-3 were analyzed. Total anti-oxidant capacity (TAC), total oxidant status (TOS), and malondialdehyde (MDA) level, and activities of catalase (CAT), superoxide dismutase (SOD) and glutathione peroxidase (GPx) were measured. Results: Enhancement in TOS, OSI, and MDA levels as well as increased in the activity of CAT and reduction in SOD and GPx activities were observed in diabetic group (D) compared with control rats. Treatment of diabetic animals with either curcumin or metformin normalized TOS, OSI, and MDA levels and restored CAT, SOD, and GPx activities. Diabetes caused extensive damages in heart tissue of rats (group D) and increased expression of caspase-3 and Bax genes and enhanced ratio of Bax/Bcl-2 expression compared with controls. Treatment with curcumin or metformin mitigated histopathological changes and dampened apoptosis by normalizing Bax and caspase-3 expression. Conclusion: Curcumin and metformin modulated diabetes-induced cardiac damage probably by reducing oxidative stress.
Effect of Isotopic Nitrogen Exchange on NTO Molecule-A DFT Approach
Authors: Türker Lemi
Published: August 2022

5-Nitro-2,4-dihydro-3H-1,2,4-triazol-3-one (NTO), is an insensitive energetic material. It is one of the most studied nitrotriazole type explosives. In the present study, a set of NTO molecules subjected to 15N exchange one at a time have been investigated in terms of energies within the realm of density functional theory at the level of B3LYP/6-311++G(d,p). The effect of isotopic exchanged type perturbation on the infra red frequencies and intensities have been searched. Also, the lactam/lactim tautomerism involving NTO and its 15N exchanged derivatives are studied and discussed.
The Foundation of Industrial Medicine of Korea, Cho Kyu-sang: One Way to Practice Catholic Social Spirituality
Authors:   Catholic Institute of Bioethics, Park Seung Mann , Kim Pyeong Man
Published: August 2022

This article investigates one way of practicing social spirituality in the medical field through the life of Francisco Xavier, Cho Kyu-sang (1925-2013). After the Second Vatican Council, the Catholic Church emphasizes the social role of the Church and teaches that the laity should fulfill their duties. In particular, medical personnel are expected to make the service to life and health their mission and are urged to pay special attention to economic, social, and cultural factors as well as medical factors that affect health.
If so, then there follows the question. How can we practice social spirituality in the medical field? The life of Cho Kyu-sang, who devoted himself to the field of industrial medicine after liberation, and to the health of workers through the industrialization era, would be one possible answer to this question. Cho Kyu-sang left some memoirettes on his life, but due to the nature of the reminiscence, there exists nontrivial missing or erroneous information. Based on the historical research and newly discovered historical records, this article restores the life of Cho Kyu-sang and ruminates the value of social spirituality that he practiced.
Fan Futures—Beyond the Archive: Papers from the FanLIS 2022 Symposium
Authors: Price Ludovica , Robinson Lyn
Published: August 2022

Following the first successful FanLIS symposium (Price & Robinson, 2022), our aim in 2022 was to continue to build bridges between the two fields, doing this through two streams held over the two-day event—the first stream being ‘Beyond the Archive’, and the second ‘Fan Futures’. ‘Beyond the Archive’ focused on the ways in which fans move beyond traditional relationships with the archive to subvert, use and perhaps even abuse the archive to create and innovate. ‘Fan Futures’ then zoomed out from the archive to consider different aspects of the information communication chain—creation, organisation, dissemination, discovery, management, preservation, analysis, use and understanding—traditional domains of concern to LIS—and how fan practice is changing and innovating in those areas.
Creating Threads, Making Archives: A Study of Organizing and Indexing Practices Around Idols’ Photos on Twitter
Authors: Das Susrita
Published: August 2022

ARMY (short for “Adorable Representative M.C. for Youth”), who are the fans of the boy band Bangtan Sonyeondan or BTS, are credited with making effective use of social media to direct fan engagement toward meeting fandom goals like trending comebacks, topping charts, and organizing charitable projects on a global scale before such fannish activities had become mainstream. While their ingenious use of social media has been the subject of much scholarly interest, the multifarious ways in which the fans organize and archive information to participate in the fandom are relatively less explored. Building on this possibility, this study analyses ARMY’s use of Twitter threads by (1) conducting a microanalysis of interactions between fans within these threads and (2) content analysis of the original posts created largely around the themes of idols’ appearance/personality, idol-idol interactions and idol-fan interactions. Closer examination of the threads reveals similarities with archival motives to shed light on important discourses in the fandom’s subcultural imagination and reflect fannish efforts at preserving “memories” of the bands’ eras or capturing interpersonal dynamics, that transform the threads into rich sites for information dissemination, much like traditional archives, although they tend to offer greater agency as curators to those who create and engage with such threads.