Fast Temporal Wavelet Graph Neural Networks

Spatio-temporal signals forecasting plays an important role in numerous domains, especially in neuroscience and transportation. The task is challenging due to the highly intricate spatial structure, as well as the non-linear temporal dynamics of the network. To facilitate reliable and timely forecast for the human brain and traffic networks, we propose the Fast Temporal Wavelet Graph Neural Networks (FTWGNN) that is both time- and memory-efficient for learning tasks on timeseries data with the underlying graph structure, thanks to the theories of multiresolution analysis and wavelet theory on discrete spaces. We employ Multiresolution Matrix Factorization (MMF) (Kondor et al., 2014) to factorize the highly dense graph structure and compute the corresponding sparse wavelet basis that allows us to construct fast wavelet convolution as the backbone of our novel architecture. Experimental results on real-world PEMS-BAY, METR-LA traffic datasets and AJILE12 ECoG dataset show that FTWGNN is competitive with the state-of-the-arts while maintaining a low computational footprint. Our PyTorch implementation is publicly available at https://github.com/HySonLab/TWGNNComment: arXiv admin note: text overlap with arXiv:2111.0194

NUMERICAL SIMULATION TO STUDY EFFECT OF DIE DESIGN PARAMETERS ON DEFORMATION POSSIBILITY OF METAL ON COMBINED DRAWING

This paper uses numerical simulation to study amethod in combined drawing process with thinning the wall when drawing of a cylindrical cup of sheet metal. The software Deform 2D is used to examineeffect of die design parameters (inclination of die) on deformation possibility of metal. Simulation results in order to select appropriate die design parameters (conical die), to enhance the ability to deform and contribute to improve product quality

VisionKG: Unleashing the Power of Visual Datasets via Knowledge Graph

The availability of vast amounts of visual data with heterogeneous features is a key factor for developing, testing, and benchmarking of new computer vision (CV) algorithms and architectures. Most visual datasets are created and curated for specific tasks or with limited image data distribution for very specific situations, and there is no unified approach to manage and access them across diverse sources, tasks, and taxonomies. This not only creates unnecessary overheads when building robust visual recognition systems, but also introduces biases into learning systems and limits the capabilities of data-centric AI. To address these problems, we propose the Vision Knowledge Graph (VisionKG), a novel resource that interlinks, organizes and manages visual datasets via knowledge graphs and Semantic Web technologies. It can serve as a unified framework facilitating simple access and querying of state-of-the-art visual datasets, regardless of their heterogeneous formats and taxonomies. One of the key differences between our approach and existing methods is that ours is knowledge-based rather than metadatabased. It enhances the enrichment of the semantics at both image and instance levels and offers various data retrieval and exploratory services via SPARQL. VisionKG currently contains 519 million RDF triples that describe approximately 40 million entities, and are accessible at https://vision.semkg.org and through APIs. With the integration of 30 datasets and four popular CV tasks, we demonstrate its usefulness across various scenarios when working with CV pipelines

Concomitant intramyocardial and hepatic hydatid cysts diagnosed by multi-modality imaging: a rare case report

Cardiac echinococcosis is a potentially fatal form of hydatid disease; yet, its diagnosis and treatment are challenging due to the variability in its clinical manifestations and due to its various unpredictable preoperative complications. Multi-modality imaging is shown to provide important guidance for the treatment and decision-making. We report a rare case of a 50-year-old woman who had concomitant cardiac and hepatic hydatid cysts. She presented with abdominal pain and elevated eosinophilic white blood cells. The initial abdominal ultrasound and computerized tomography revealed a large cyst in the liver. An intramyocardial cyst was detected by two-dimensional echocardiography. Three-dimensional echocardiography increased the confidence level of two-dimensional echocardiography by displaying the three-dimensional volume of the cyst and allowing visualization of its spatial characteristics and the relationships with adjacent cardiac structures, which was subsequently confirmed at surgery. Multi-detector computed tomography and magnetic resonance imaging helped localize and define the typical morphological features of the cyst. Serology and antigen detection were used for diagnosis. This rare case underlines the integration of clinical, multi-modality imaging, and pathological data in the diagnosis of concomitant intramyocardial and hepatic hydatid cysts. Surgical resection of cysts and anthelmintic medication were successful in the management of this patient

Survey on Vietnamese teachers’ perspectives and perceived support during COVID-19

The COVID-19 pandemic has caused unprecedented damage to the educational system worldwide. Besides the measurable economic impacts in the short-term and long-term, there is intangible destruction within educational institutions. In particular, teachers – the most critical intellectual resources of any schools – have to face various types of financial, physical, and mental struggles due to COVID-19. To capture the current context of more than one million Vietnamese teachers during COVID-19, we distributed an e- survey to more than 2,500 randomly selected teachers from two major teacher communities on Facebook from 6th to 11th April 2020. From over 373 responses, we excluded the observations which violated our cross-check questions and retained 294 observations for further analysis. This dataset includes: (i) Demographics of participants; (ii) Teachers' perspectives regarding the operation of teaching activities during the pandemic; (iii) Teachers' received support from their schools, government bodies, other stakeholders such as teacher unions, and parents' associations; and (iv) teachers' evaluation of school readiness toward digital transformation. Further, the dataset was supplemented with an additional question on the teachers' primary source of professional development activities during the pandemic

EFFECT OF PRO-OXIDANT ADDITIVES ON DEGRADATION OF MULCH FILM BASED ON RECYCLED POLYETHYLENE

The effect of pro-oxidant additives (Iron, Cobalt and Manganese stearates) on the biodegradation of recycle polyethelene mulching films was studied in both accelerated weather and natural exposure conditions. The degradation degree of film was determined by measuring mechanical properties and scanning electronic microscope (SEM). The results showed that the mechanical properties of film samples with pro-oxirant additives decreased rapidly, and that surface film with additives was degraded clearly compared to the films without additives after 30 cycles of accelerated weather. Reliability in terms of acceleration are 28 - 30 cycles of exposure and in the natural conditions reached 10-12 months

Concomitant intramyocardial and hepatic hydatid cysts diagnosed by multi-modality imaging: A rare case report

Cardiac echinococcosis is a potentially fatal form of hydatid disease; yet, its diagnosis and treatment are challenging due to the variability in its clinical manifestations and due to its various unpredictable preoperative complications. Multi-modality imaging is shown to provide important guidance for the treatment and decision-making. We report a rare case of a 50-year-old woman who had concomitant cardiac and hepatic hydatid cysts. She presented with abdominal pain and elevated eosinophilic white blood cells. The initial abdominal ultrasound and computerized tomography revealed a large cyst in the liver. An intramyocardial cyst was detected by two-dimensional echocardiography. Three-dimensional echocardiography increased the confidence level of two-dimensional echocardiography by displaying the three-dimensional volume of the cyst and allowing visualization of its spatial characteristics and the relationships with adjacent cardiac structures, which was subsequently confirmed at surgery. Multi-detector computed tomography and magnetic resonance imaging helped localize and define the typical morphological features of the cyst. Serology and antigen detection were used for diagnosis. This rare case underlines the integration of clinical, multi-modality imaging, and pathological data in the diagnosis of concomitant intramyocardial and hepatic hydatid cysts. Surgical resection of cysts and anthelmintic medication were successful in the management of this patient

Assessment of aflatoxin B1 contamination in rice and maize

Introduction: Aflatoxins B1 are among the most common poisonous mycotoxins produced by certain fungi that harm animals and crops. Mycotoxins can cause a variety of adverse health effects and pose a serious health threat to humans. The Maximum Residue Limits of aflatoxin B1 in processed cereals and ingredients are 2 parts per billion (ppb) and 5 ppb, respectively. Objectives: To evaluate the status of aflatoxin B 1 contamination in rice, corn and staple food produced in Ha Giang province compared with the maximum permitted levels. Methods: A total of 210 rice and maize samples were analyzed to quantify the level of aflatoxin B1. Analysis of mycotoxins was conducted by High Performance Liquid Chromatography using a fluorescence detector. Results: It was found that rice, rice products, maize, and maize products had a mean aflatoxin B1 content of 1.79 ppb, 2.55 ppb, 2.19 ppb, and 6.35 ppb, respectively. The results also showed that 71.9% of samples were contaminated with mycotoxins, and 14.28% of samples exceeded the maximum allowable limit. Conclusion: The concentration of aflatoxin B1 in 14.28% of the samples are over permissible limits by nationwide regulations

Effects of water scarcity awareness and climate change belief on recycled water usage willingness: Evidence from New Mexico, United States

The global water crisis is being exacerbated by climate change, even in the United States. Recycled water is a feasible alternative to alleviate the water shortage, but it is constrained by humans’ perceptions. The current study examines how residents’ water scarcity awareness and climate change belief influence their willingness to use recycled water directly and indirectly. Bayesian Mindsponge Framework (BMF) analytics was employed on a dataset of 1831 residents in Albuquerque, New Mexico, an arid inland region in the US. We discovered that residents’ willingness to use direct recycled potable water is positively affected by their awareness of water scarcity, but the effect is conditional on their belief in the impacts of climate change on the water cycle. Meanwhile, the willingness to use indirect recycled potable water is influenced by water scarcity awareness, and the belief in climate change further enhances this effect. These findings implicate that fighting climate change denialism and informing the public of the water scarcity situation in the region can contribute to the effectiveness and sustainability of long-term water conservation and climate change alleviation efforts