CR10—A PUBLIC DATABASE OF COSMIC RADIATION MEASUREMENTS AT AVIATION ALTITUDES OF ABOUT 10 KM

Abstract Long-term measurements using silicon radiation spectrometer Liulin on board commercial aircraft have been performed since 2001; results were put into a new database, which covers more than 4500 flights with more than 130 000 measurements. Methodology and tools were developed to normalize the data with respect to latitude and altitude and thus enable comparison with other radiation detectors and with model calculations. This capability is demonstrated using data from the neutron monitor at Lomnický štít. Instead of providing data files for individual measurement period, two software solutions are delivered. First is a web-based user interface for visualizing and downloading arbitrary time window of interest from the database hosted at http://cr10.odz.ujf.cas.cz. The second is a set of interactive Python notebooks available at GitHub. Those implement the calibration, normalization and visualization methods—so the outputs can be tailored to user needs. The software and data are provided under GNU/CC license.

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Design and Development of a Web-based Delirium Preventive Application for Long-term Care Facilities: A Methodological Study (Preprint)

10.2196/preprints.26092 ◽

2020 ◽

Author(s):

Kyoung Ja Moon ◽

Chang-Sik Son ◽

Jong-Ha Lee ◽

Mina Park

Keyword(s):

Risk Factors ◽

Long Term Care ◽

Cloud System ◽

Evidence Based ◽

Methodological Study ◽

Term Care ◽

Web Based ◽

Care Facilities ◽

Delirium Prevention

BACKGROUND Long-term care facilities demonstrate low levels of knowledge and care for patients with delirium and are often not properly equipped with an electronic medical record system, thereby hindering systematic approaches to delirium monitoring. OBJECTIVE This study aims to develop a web-based delirium preventive application (app), with an integrated predictive model, for long-term care (LTC) facilities using artificial intelligence (AI). METHODS This methodological study was conducted to develop an app and link it with the Amazon cloud system. The app was developed based on an evidence-based literature review and the validity of the AI prediction model algorithm. Participants comprised 206 persons admitted to LTC facilities. The app was developed in 5 phases. First, through a review of evidence-based literature, risk factors for predicting delirium and non-pharmaceutical contents for preventive intervention were identified. Second, the app, consisting of several screens, was designed; this involved providing basic information, predicting the onset of delirium according to risk factors, assessing delirium, and intervening for prevention. Third, based on the existing data, predictive analysis was performed, and the algorithm developed through this was calculated at the site linked to the web through the Amazon cloud system and sent back to the app. Fourth, a pilot test using the developed app was conducted with 33 patients. Fifth, the app was finalized. RESULTS We developed the Web_DeliPREVENT_4LCF for patients of LTC facilities. This app provides information on delirium, inputs risk factors, predicts and informs the degree of delirium risk, and enables delirium measurement or delirium prevention interventions to be immediately implemented with a verified tool. CONCLUSIONS This web-based application is evidence-based and offers easy mobilization and care to patients with delirium in LTC facilities. Therefore, the use of this app improves the unrecognized of delirium and predicts the degree of delirium risk, thereby helping initiatives for delirium prevention and providing interventions. This would ultimately improve patient safety and quality of care. CLINICALTRIAL none

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Clinical impact of myositis-specific autoantibodies on long-term prognosis of juvenile idiopathic inflammatory myopathies: multicentre study

Rheumatology ◽

10.1093/rheumatology/keab108 ◽

2021 ◽

Author(s):

Yuichi Yamasaki ◽

Norimoto Kobayashi ◽

Shinji Akioka ◽

Kazuko Yamazaki ◽

Shunichiro Takezaki ◽

...

Keyword(s):

Matrix Protein ◽

Multiple Drug ◽

Idiopathic Inflammatory Myopathies ◽

Inflammatory Myopathies ◽

Gamma Subunits ◽

Specific Autoantibody ◽

Long Term Prognosis ◽

Using Data ◽

Drug Free

Abstract Objectives This study aimed to investigate the clinical characteristics, treatment and prognosis of juvenile idiopathic inflammatory myopathies (JIIM) in Japan for each myositis-specific autoantibody (MSA) profile. Methods A multicentre, retrospective study was conducted using data of patients with JIIM at nine paediatric rheumatology centres in Japan. Patients with MSA profiles, determined by immunoprecipitation using stored serum from the active stage, were included. Results MSA were detected in 85 of 96 cases eligible for the analyses. Over 90% of the patients in this study had one of the following three MSA types: anti-melanoma differentiation-associated protein 5 (MDA5) (n = 31), anti-transcriptional intermediary factor 1 alpha and/or gamma subunits (TIF1γ) (n = 25) and anti-nuclear matrix protein 2 (NXP2) (n = 25) antibodies. Gottron papules and periungual capillary abnormalities were the most common signs of every MSA group in the initial phase. The presence of interstitial lung disease (ILD) was the highest risk factor for patients with anti-MDA5 antibodies. Most patients were administered multiple drug therapies: glucocorticoids and MTX were administered to patients with anti-TIF1γ or anti-NXP2 antibodies. Half of the patients with anti-MDA5 antibodies received more than three medications including i.v. CYC, especially patients with ILD. Patients with anti-MDA5 antibodies were more likely to achieve drug-free remission (29 vs 21%) and less likely to relapse (26 vs 44%) than others. Conclusion Anti-MDA5 antibodies are the most common MSA type in Japan, and patients with this antibody are characterized by ILD at onset, multiple medications including i.v. CYC, drug-free remission, and a lower frequency of relapse. New therapeutic strategies are required for other MSA types.

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Increase associated risk of gynaecological cancer due to long-term exposure to high concentration of atmospheric SO2 industrial pollutant

Indoor and Built Environment ◽

10.1177/1420326x211003655 ◽

2021 ◽

pp. 1420326X2110036

Author(s):

Qian Xu ◽

Chan Lu ◽

Rachael Gakii Murithi ◽

Lanqin Cao

Keyword(s):

Time Windows ◽

Air Pollutant ◽

Gynaecological Cancer ◽

High Concentration ◽

The Past ◽

Short And Long Term ◽

Using Data ◽

Air Quality Monitoring Stations ◽

Control Study

A cohort case–control study was conducted in XiangYa Hospital, Changsha, China, which involved 305 patients and 399 healthy women, from June 2010 to December 2018, to evaluate the association between Chinese women’s short- and long-term exposure to industrial air pollutant, SO2 and gynaecological cancer (GC). We obtained personal and family information from the XiangYa Hospital electronic computer medical records. Using data obtained from the air quality monitoring stations in Changsha, we estimated each woman’s exposure to the industrial air pollutant, sulphur dioxide (SO2), for different time windows, including the past 1, 5, 10 and 15 years before diagnosis of the disease. A multiple logistic regression model was used to assess the association between GC and SO2 exposure. GC was significantly associated with long-term SO2 exposure, with adjusted odds ratio (95% confidence interval) = 1.56 (1.10–2.21) and 1.81 (1.07–3.06) for a per interquartile range increase in the past 10 and 15 years, respectively. Sensitivity analysis showed that different groups reacted in different ways to long-term SO2 exposure. We concluded that long-term exposure to high concentration of industrial pollutant, SO2 is associated with the development of GC. This finding has implications for the prevention and reduction of GC.

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Assisting scalable diagnosis automatically via CT images in the combat against COVID-19

Scientific Reports ◽

10.1038/s41598-021-83424-5 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Bohan Liu ◽

Pan Liu ◽

Lutao Dai ◽

Yanlin Yang ◽

Peng Xie ◽

...

Keyword(s):

Large Scale ◽

Area Under The Curve ◽

Independent Set ◽

Reference Method ◽

Ct Images ◽

Loss Of Life ◽

Case Identification ◽

Reverse Transcription Pcr ◽

Using Data

AbstractThe pandemic of Coronavirus Disease 2019 (COVID-19) is causing enormous loss of life globally. Prompt case identification is critical. The reference method is the real-time reverse transcription PCR (RT-PCR) assay, whose limitations may curb its prompt large-scale application. COVID-19 manifests with chest computed tomography (CT) abnormalities, some even before the onset of symptoms. We tested the hypothesis that the application of deep learning (DL) to 3D CT images could help identify COVID-19 infections. Using data from 920 COVID-19 and 1,073 non-COVID-19 pneumonia patients, we developed a modified DenseNet-264 model, COVIDNet, to classify CT images to either class. When tested on an independent set of 233 COVID-19 and 289 non-COVID-19 pneumonia patients, COVIDNet achieved an accuracy rate of 94.3% and an area under the curve of 0.98. As of March 23, 2020, the COVIDNet system had been used 11,966 times with a sensitivity of 91.12% and a specificity of 88.50% in six hospitals with PCR confirmation. Application of DL to CT images may improve both efficiency and capacity of case detection and long-term surveillance.

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Long-term effectiveness in patients previously treated with cladribine tablets: a real-world analysis of the Italian multiple sclerosis registry (CLARINET-MS)

Therapeutic Advances in Neurological Disorders ◽

10.1177/1756286420922685 ◽

2020 ◽

Vol 13 ◽

pp. 175628642092268 ◽

Cited By ~ 1

Author(s):

Francesco Patti ◽

Andrea Visconti ◽

Antonio Capacchione ◽

Sanjeev Roy ◽

Maria Trojano ◽

...

Keyword(s):

Multiple Sclerosis ◽

Real World ◽

Event Analysis ◽

Treatment Change ◽

Real World Data ◽

Indirect Measure ◽

Disease Modifying Drugs ◽

Disease Modifying ◽

Using Data

Background: The CLARINET-MS study assessed the long-term effectiveness of cladribine tablets by following patients with multiple sclerosis (MS) in Italy, using data from the Italian MS Registry. Methods: Real-world data (RWD) from Italian MS patients who participated in cladribine tablets randomised clinical trials (RCTs; CLARITY, CLARITY Extension, ONWARD or ORACLE-MS) across 17 MS centres were obtained from the Italian MS Registry. RWD were collected during a set observation period, spanning from the last dose of cladribine tablets during the RCT (defined as baseline) to the last visit date in the registry, treatment switch to other disease-modifying drugs, date of last Expanded Disability Status Scale recording or date of the last relapse (whichever occurred last). Time-to-event analysis was completed using the Kaplan–Meier (KM) method. Median duration and associated 95% confidence intervals (CI) were estimated from the model. Results: Time span under observation in the Italian MS Registry was 1–137 (median 80.3) months. In the total Italian patient population ( n = 80), the KM estimates for the probability of being relapse-free at 12, 36 and 60 months after the last dose of cladribine tablets were 84.8%, 66.2% and 57.2%, respectively. The corresponding probability of being progression-free at 60 months after the last dose was 63.7%. The KM estimate for the probability of not initiating another disease-modifying treatment at 60 months after the last dose of cladribine tablets was 28.1%, and the median time-to-treatment change was 32.1 (95% CI 15.5–39.5) months. Conclusion: CLARINET-MS provides an indirect measure of the long-term effectiveness of cladribine tablets. Over half of MS patients analysed did not relapse or experience disability progression during 60 months of follow-up from the last dose, suggesting that cladribine tablets remain effective in years 3 and 4 after short courses at the beginning of years 1 and 2.

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First-Line Atezolizumab Plus Bevacizumab versus Sorafenib in Hepatocellular Carcinoma: A Cost-Effectiveness Analysis

Cancers ◽

10.3390/cancers13050931 ◽

2021 ◽

Vol 13 (5) ◽

pp. 931

Author(s):

Chi-Leung Chiang ◽

Sik-Kwan Chan ◽

Shing-Fung Lee ◽

Horace Cheuk-Wai Choi

Keyword(s):

Hepatocellular Carcinoma ◽

Cost Effectiveness ◽

Lifetime Cost ◽

Cost Effective ◽

First Line ◽

First Line Therapy ◽

Payer Perspective ◽

Life Years ◽

Using Data

Background: The IMbrave 150 trial revealed that atezolizumab plus bevacizumab (atezo–bev) improves survival in patients with unresectable hepatocellular carcinoma (HCC) (1 year survival rate: 67.2% vs. 54.6%). We assessed the cost-effectiveness of atezo–bev vs. sorafenib as first-line therapy in patients with unresectable HCC from the US payer perspective. Methods: Using data from the IMbrave 150, we developed a Markov model to compare the lifetime cost and efficacy of atezo–bev as first-line systemic therapy in HCC with those of sorafenib. The main outcomes were life-years, quality-adjusted life-years (QALYs), lifetime costs, and incremental cost-effectiveness ratio (ICER). Results: Atezo–bev demonstrated a gain of 0.44 QALYs, with an additional cost of USD 79,074. The ICER of atezo–bev was USD 179,729 per QALY when compared with sorafenib. The model was most sensitive to the overall survival hazard ratio and body weight. If we assumed that all patients at the end of the IMbrave 150 trial were cured of HCC, atezo–bev was cost-effective (ICER USD 53,854 per QALY). However, if all patients followed the Surveillance, Epidemiology, and End Results data, the ICER of atezo–bev was USD 385,857 per QALY. Reducing the price of atezo–bev by 20% and 29% would satisfy the USD 150,000/QALY and 100,000/QALY willingness-to-pay threshold. Moreover, capping the duration of therapy to ≤12 months or reducing the dosage of bev to ≤10 mg/kg would render atezo–bev cost-effective. Conclusions: The long-term effectiveness of atezo–bev is a critical but uncertain determinant of its cost-effectiveness. Price reduction would favorably influence cost-effectiveness, even if long-term clinical outcomes were modest. Further studies to optimize the duration and dosage of therapy are warranted.

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Long-Term Development of Urban Agriculture: Resilience and Sustainability of Farmers Facing the Covid-19 Pandemic in Japan

Sustainability ◽

10.3390/su13084316 ◽

2021 ◽

Vol 13 (8) ◽

pp. 4316

Author(s):

Shingo Yoshida ◽

Hironori Yagi

Keyword(s):

Urban Agriculture ◽

Food Systems ◽

Direct Marketing ◽

Farming System ◽

Long Term Effects ◽

Short Term ◽

Short Supply ◽

Using Data ◽

Urban People

The coronavirus disease 2019 (Covid-19) pandemic has forced global food systems to face unprecedented uncertain shocks even in terms of human health. Urban agriculture is expected to be more resilient because of its short supply chain for urban people and diversified farming activities. However, the short-and long-term effects of the Covid-19 pandemic on urban farms remain unclear. This study aims to reveal the conditions for farm resilience to the Covid-19 pandemic in 2020 and the relationship between short-term farm resilience and long-term farm development using data from a survey of 74 farms located in Tokyo. The results are as follows. First, more than half of the sample farms increased their farm sales during this period. This resilience can be called the “persistence” approach. Second, short-term farm resilience and other sustainable farm activities contributed to improving farmers’ intentions for long-term farm development and farmland preservation. Third, the most important resilience attributes were the direct marketing, entrepreneurship, and social networks of farmers. We discussed the necessity of building farmers’ transformative capabilities for a more resilient urban farming system. These results imply that support to enhance the short-term resilience of urban farms is worth more than the short-term profit of the farms.

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Asymmetric competition causes multimodal size distributions in spatially structured populations

Proceedings of The Royal Society B Biological Sciences ◽

10.1098/rspb.2015.2404 ◽

2016 ◽

Vol 283 (1823) ◽

pp. 20152404 ◽

Cited By ~ 2

Author(s):

Jorge Velázquez ◽

Robert B. Allen ◽

David A. Coomes ◽

Markus P. Eichhorn

Keyword(s):

Resource Competition ◽

Structured Populations ◽

Necessary Condition ◽

Small Scale ◽

Asymmetric Competition ◽

Size Distributions ◽

Long Term Study ◽

Multimodal Distributions ◽

Using Data

Plant sizes within populations often exhibit multimodal distributions, even when all individuals are the same age and have experienced identical conditions. To establish the causes of this, we created an individual-based model simulating the growth of trees in a spatially explicit framework, which was parametrized using data from a long-term study of forest stands in New Zealand. First, we demonstrate that asymmetric resource competition is a necessary condition for the formation of multimodal size distributions within cohorts. By contrast, the legacy of small-scale clustering during recruitment is transient and quickly overwhelmed by density-dependent mortality. Complex multi-layered size distributions are generated when established individuals are restricted in the spatial domain within which they can capture resources. The number of modes reveals the effective number of direct competitors, while the separation and spread of modes are influenced by distances among established individuals. Asymmetric competition within local neighbourhoods can therefore generate a range of complex size distributions within even-aged cohorts.

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Labor Market Effects of Marijuana and Cocaine Use among Young Men

ILR Review ◽

10.1177/001979399204500302 ◽

1992 ◽

Vol 45 (3) ◽

pp. 435-448 ◽

Cited By ~ 38

Author(s):

Charles A. Register ◽

Donald R. Williams

Keyword(s):

Labor Market ◽

Drug Use ◽

Longitudinal Survey ◽

National Longitudinal Survey ◽

Productivity Effect ◽

Cocaine Use ◽

Market Effects ◽

Net Productivity ◽

Using Data

Using data on marijuana and cocaine use from the 1984 National Longitudinal Survey of Youth, the authors examine the hypothesis that drug use reduces labor market productivity, as measured by wages. From an analysis that controls for the probability of employment and the endogeneity of drug use, they find that although long-term and on-the-job use of marijuana negatively affected wages, the net productivity effect for all marijuana users (both those who engaged in long-term or on-the-job use and those who did not) was positive. No statistically significant association was found between cocaine use and productivity.

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IAGOS Research Infrastructure for Global-Scale Atmosphere Monitoring by Instrumented Passenger Aircraft

10.5194/dach2022-251 ◽

2021 ◽

Author(s):

Andreas Petzold ◽

Valerie Thouret ◽

Christoph Gerbig ◽

Andreas Zahn ◽

Martin Gallagher ◽

...

Keyword(s):

Climate Change ◽

Air Quality ◽

Relative Humidity ◽

Water Vapour ◽

Research Infrastructure ◽

Good Resolution ◽

European Research ◽

Commercial Aircraft ◽

High Quality

IAGOS (www.iagos.org) is a European Research Infrastructure using commercial aircraft (Airbus A340, A330, and soon A350) for automatic and routine measurements of atmospheric composition including reactive gases (ozone, carbon monoxide, nitrogen oxides, volatile organic compounds), greenhouse gases (water vapour, carbon dioxide, methane), aerosols and cloud particles along with essential thermodynamic parameters. The main objective of IAGOS is to provide the most complete set of high-quality essential climate variables (ECV) covering several decades for the long-term monitoring of climate and air quality. The observations are stored in the IAGOS data centre along with added-value products to facilitate the scientific interpretation of the data. IAGOS began as two European projects, MOZAIC and CARIBIC, in the early 1990s. These projects demonstrated that commercial aircraft are ideal platforms for routine atmospheric measurements. IAGOS then evolved as a European Research Infrastructure offering a mature and sustainable organization for the benefits of the scientific community and for the operational services in charge of air quality and climate change issues such as the Copernicus Atmosphere Monitoring Services (CAMS) and the Copernicus Climate Change Service (C3S). IAGOS is also a contributing network of the World Meteorological Organization (WMO). IAGOS provides measurements of numerous chemical compounds which are recorded simultaneously in the critical region of the upper troposphere &#8211; lower stratosphere (UTLS) and geographical regions such as Africa and the mid-Pacific which are poorly sampled by other means. The data are used by hundreds of groups worldwide performing data analysis for climatology and trend studies, model evaluation, satellite validation and the study of detailed chemical and physical processes around the tropopause. IAGOS data also play an important role in the re-assessment of the climate impact of aviation. Most important in the context of weather-related research, IAGOS and its predecessor programmes provide long-term observations of water vapour and relative humidity with respect to ice in the UTLS as well as throughout the tropospheric column during climb-out and descending phases around airports, now for more than 25 years. The high quality and very good resolution of IAGOS observations of relative humidity over ice are used to better understand the role of water vapour and of ice-supersaturated air masses in the tropopause region and to improve their representation in numerical weather and climate forecasting models. Furthermore, CAMS is using the water vapour vertical profiles in near real time for the continuous validation of the CAMS atmospheric models.

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