A spatially explicit, multi-scale occupancy model for large-scale population monitoring

In this Opinion, the importance of public awareness to design solutions to mitigate climate change issues is highlighted. A large-scale acknowledgment of the climate change consequences has great potential to build social momentum. Momentum, in turn, builds motivation and demand, which can be leveraged to develop a multi-scale strategy to tackle the issue. The pursuit of public awareness is a valuable addition to the scientific approach to addressing climate change issues. The Opinion is concluded by providing strategies on how to effectively raise public awareness on climate change-related topics through an integrated, well-connected network of mavens (e.g., scientists) and connectors (e.g., social media influencers).

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Thyroidectomy for thyroid cancer via transareola single-site endoscopic approach: results of a case-match study with large-scale population

Surgical Endoscopy ◽

10.1007/s00464-021-08424-y ◽

2021 ◽

Author(s):

Juyong Liang ◽

Ling Zhan ◽

Ming Xuan ◽

Qiwu Zhao ◽

Lingxie Chen ◽

...

Keyword(s):

Thyroid Cancer ◽

Large Scale ◽

Endoscopic Approach ◽

Single Site ◽

Scale Population

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Multi-Scale Ionospheric Anomalies Monitoring and Spatio-Temporal Analysis during Intense Storm

Atmosphere ◽

10.3390/atmos12020215 ◽

2021 ◽

Vol 12 (2) ◽

pp. 215

Author(s):

Na Cheng ◽

Shuli Song ◽

Wei Li

Keyword(s):

Magnetic Storm ◽

Large Scale ◽

Temporal Dynamics ◽

Ionospheric Disturbance ◽

Ionospheric Scintillation ◽

Small Scale ◽

Electron Content ◽

Total Electron ◽

Multi Scale ◽

Intense Storm

The ionosphere is a significant component of the geospace environment. Storm-induced ionospheric anomalies severely affect the performance of Global Navigation Satellite System (GNSS) Positioning, Navigation, and Timing (PNT) and human space activities, e.g., the Earth observation, deep space exploration, and space weather monitoring and prediction. In this study, we present and discuss the multi-scale ionospheric anomalies monitoring over China using the GNSS observations from the Crustal Movement Observation Network of China (CMONOC) during the 2015 St. Patrick’s Day storm. Total Electron Content (TEC), Ionospheric Electron Density (IED), and the ionospheric disturbance index are used to monitor the storm-induced ionospheric anomalies. This study finally reveals the occurrence of the large-scale ionospheric storms and small-scale ionospheric scintillation during the storm. The results show that this magnetic storm was accompanied by a positive phase and a negative phase ionospheric storm. At the beginning of the main phase of the magnetic storm, both TEC and IED were significantly enhanced. There was long-duration depletion in the topside ionospheric TEC during the recovery phase of the storm. This study also reveals the response and variations in regional ionosphere scintillation. The Rate of the TEC Index (ROTI) was exploited to investigate the ionospheric scintillation and compared with the temporal dynamics of vertical TEC. The analysis of the ROTI proved these storm-induced TEC depletions, which suppressed the occurrence of the ionospheric scintillation. To improve the spatial resolution for ionospheric anomalies monitoring, the regional Three-Dimensional (3D) ionospheric model is reconstructed by the Computerized Ionospheric Tomography (CIT) technique. The spatial-temporal dynamics of ionospheric anomalies during the severe geomagnetic storm was reflected in detail. The IED varied with latitude and altitude dramatically; the maximum IED decreased, and the area where IEDs were maximum moved southward.

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Publisher Correction: A link between appendectomy and gastrointestinal cancers: a large-scale population-based cohort study in Korea

Scientific Reports ◽

10.1038/s41598-021-85952-6 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Youn Young Park ◽

Kil‑yong Lee ◽

Seong Taek Oh ◽

Sang Hyun Park ◽

Kyung Do Han ◽

...

Keyword(s):

Cohort Study ◽

Large Scale ◽

Population Based ◽

Gastrointestinal Cancers ◽

Scale Population

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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Multi-scale modelling of a large scale shell-and-tube latent heat storage system for direct steam generation power plants

10.1063/5.0028816 ◽

2020 ◽

Author(s):

Clément Beust ◽

Erwin Franquet ◽

Jean-Pierre Bédécarrats ◽

Pierre Garcia ◽

Jérôme Pouvreau ◽

...

Keyword(s):

Power Plants ◽

Large Scale ◽

Storage System ◽

Steam Generation ◽

Latent Heat Storage ◽

Multi Scale ◽

Direct Steam ◽

Scale Modelling ◽

Shell And Tube ◽

Generation Power

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Using Bus Ticketing Big Data to Investigate the Behaviors of the Population Flow of Chinese Suburban Residents in the Post-COVID-19 Phase

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18116066 ◽

2021 ◽

Vol 18 (11) ◽

pp. 6066

Author(s):

Yanbing Bai ◽

Lu Sun ◽

Haoyu Liu ◽

Chao Xie

Keyword(s):

Travel Behavior ◽

Large Scale ◽

Behavior Patterns ◽

Population Movements ◽

Economic Level ◽

Passenger Travel ◽

Scale Population ◽

Travel Behaviors ◽

Railway Passenger ◽

And Control

Large-scale population movements can turn local diseases into widespread epidemics. Grasping the characteristic of the population flow in the context of the COVID-19 is of great significance for providing information to epidemiology and formulating scientific and reasonable prevention and control policies. Especially in the post-COVID-19 phase, it is essential to maintain the achievement of the fight against the epidemic. Previous research focuses on flight and railway passenger travel behavior and patterns, but China also has numerous suburban residents with a not-high economic level; investigating their travel behaviors is significant for national stability. However, estimating the impacts of the COVID-19 for suburban residents’ travel behaviors remains challenging because of lacking apposite data. Here we submit bus ticketing data including approximately 26,000,000 records from April 2020–August 2020 for 2705 stations. Our results indicate that Suburban residents in Chinese Southern regions are more likely to travel by bus, and travel frequency is higher. Associated with the economic level, we find that residents in the economically developed region more likely to travel or carry out various social activities. Considering from the perspective of the traveling crowd, we find that men and young people are easier to travel by bus; however, they are exactly the main workforce. The indication of our findings is that suburban residents’ travel behavior is affected profoundly by economy and consistent with the inherent behavior patterns before the COVID-19 outbreak. We use typical regions as verification and it is indeed the case.

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Integrating landscape resistance and multi-scale predictor of habitat selection for amphibian distribution modelling at large scale

Landscape Ecology ◽

10.1007/s10980-021-01327-2 ◽

2021 ◽

Author(s):

Florence Matutini ◽

Jacques Baudry ◽

Marie-Josée Fortin ◽

Guillaume Pain ◽

Joséphine Pithon

Keyword(s):

Habitat Selection ◽

Large Scale ◽

Landscape Resistance ◽

Distribution Modelling ◽

Multi Scale ◽

Selection For

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Hybrid Graph Neural Networks for Crowd Counting

Proceedings of the AAAI Conference on Artificial Intelligence ◽

10.1609/aaai.v34i07.6839 ◽

2020 ◽

Vol 34 (07) ◽

pp. 11693-11700 ◽

Cited By ~ 2

Author(s):

Ao Luo ◽

Fan Yang ◽

Xin Li ◽

Dong Nie ◽

Zhicheng Jiao ◽

...

Keyword(s):

Network Architecture ◽

Message Passing ◽

Large Scale ◽

State Of The Art ◽

Density Variation ◽

Feature Maps ◽

Crowd Counting ◽

Multi Scale ◽

Crowd Density ◽

Graph Neural Networks

Crowd counting is an important yet challenging task due to the large scale and density variation. Recent investigations have shown that distilling rich relations among multi-scale features and exploiting useful information from the auxiliary task, i.e., localization, are vital for this task. Nevertheless, how to comprehensively leverage these relations within a unified network architecture is still a challenging problem. In this paper, we present a novel network structure called Hybrid Graph Neural Network (HyGnn) which targets to relieve the problem by interweaving the multi-scale features for crowd density as well as its auxiliary task (localization) together and performing joint reasoning over a graph. Specifically, HyGnn integrates a hybrid graph to jointly represent the task-specific feature maps of different scales as nodes, and two types of relations as edges: (i) multi-scale relations capturing the feature dependencies across scales and (ii) mutual beneficial relations building bridges for the cooperation between counting and localization. Thus, through message passing, HyGnn can capture and distill richer relations between nodes to obtain more powerful representations, providing robust and accurate results. Our HyGnn performs significantly well on four challenging datasets: ShanghaiTech Part A, ShanghaiTech Part B, UCF_CC_50 and UCF_QNRF, outperforming the state-of-the-art algorithms by a large margin.

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Maternal adherence to micronutrient supplementation before and during pregnancy in Northwest China: a large-scale population-based cross-sectional survey

BMJ Open ◽

10.1136/bmjopen-2018-028843 ◽

2019 ◽

Vol 9 (8) ◽

pp. e028843 ◽

Cited By ~ 6

Author(s):

Danmeng Liu ◽

Yue Cheng ◽

Shaonong Dang ◽

Duolao Wang ◽

Yaling Zhao ◽

...

Keyword(s):

Pregnant Women ◽

Large Scale ◽

Northwest China ◽

Population Based ◽

Shaanxi Province ◽

Micronutrient Supplementation ◽

Cross Sectional Survey ◽

Start Time ◽

Cross Sectional ◽

Scale Population

ObjectivesTo report the situation of maternal micronutrient supplementation before and during pregnancy in Northwest China and to examine the rates of and factors related to the adherence to micronutrient supplementation among pregnant women in this region, where dietary micronutrient intake is commonly insufficient.DesignA large-scale population-based cross-sectional survey.SettingTwenty counties and ten districts of Shaanxi Province.ParticipantsA sample of 30 027 women were selected using a stratified multistage random sampling method. A total of 28 678 women were chosen for the final analysis after excluding those who did not provide clear information about nutritional supplementation before and during pregnancy.Main outcome measuresMaternal adherence to micronutrient supplementation (high and low) were the outcomes. They were determined by the start time and duration of use according to Chinese guidelines (for folic acid (FA) supplements) and WHO recommendations (for iron, calcium and multiple-micronutrient (MMN) supplements).ResultsIn total, 83.9% of women took at least one kind of micronutrient supplement before or during pregnancy. FA (67.6%) and calcium (57.5%) were the primarily used micronutrient supplements; few participants used MMN (14.0%) or iron (5.4%). Adherence to supplementation of all micronutrients was low (7.4% for FA, 0.6% for iron, 11.7% for calcium and 2.7% for MMN). Higher educational levels, higher income levels, urban residence and better antenatal care (including pregnancy consultation and a higher frequency of antenatal visits) were associated with high adherence to micronutrient supplementation.ConclusionMaternal micronutrient supplementation before and during pregnancy in Northwest China was way below standards recommended by the Chinese guidelines or WHO. Targeted health education and future nutritional guidelines are suggested to improve this situation, especially in pregnant women with disadvantaged sociodemographic conditions.

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