Identifying the time scale of temporal association

1988 ◽  
Vol 66 (9) ◽  
pp. 2090-2092 ◽  
Author(s):  
Austin Burt ◽  
Wayne Hunte ◽  
France Dufresne
Keyword(s):  
Time Scale ◽  
Quantitative Description ◽  
Temporal Association ◽  
Time Interval ◽  
Thalassoma Bifasciatum ◽  
Spawning Frequency ◽  
Initial Event ◽  
Novel Method ◽  
Using Data

Previously used methods of investigating the temporal association of behavioural events have tested sequences of events for temporal clumping; such an approach does not quantitatively indicate the time scale over which the association is significant. We present a novel method of analysis that specifically identifies this time scale, thereby allowing more ready elimination of competing causal hypotheses for the association observed. Our null hypothesis is that, following any event, the number of events in a given time interval is independent of the time elapsed since the initial event. The method is simple and robust against long-term changes in event frequency, and provides a more detailed quantitative description of the temporal association. We illustrate it using data on spawning in the blueheaded wrasse (Thalassoma bifasciatum). The analysis demonstrates that, after a spawning event, there is a 70% increase in mean spawning frequency which lasts for 30 s and then abruptly disappears. The effect of spawns appears to summate multiplicatively.

A New Approach to the Long-Term Activity Behavior of DM UMa

2012 ◽  
Vol 21 (4) ◽  
Author(s):  
G. Taş ◽  
S. Evren
Keyword(s):  
Broad Band ◽  
Color Variation ◽  
Time Interval ◽  
Period Analysis ◽  
New Approach ◽  
V Band ◽  
Photometric Observations ◽  
Color Data ◽  
Using Data

AbstractA long-term activity character of DM UMa (K0-1 IV-III), which is one of the most active members of the RS CVn type variables, is examined using the multicolor photometric observations which spread to the time interval between 1980 and 2009. In this work, we present a new approximation for the long-term light and color variation of DM UMa using data obtained by combining our own observations obtained in the Johnson broad-band U,B,V,R filters between the years 1997 and 2008 and data published in literature. Available light and color data were examined for the long-term and seasonal variations using PERIOD04 program. The period analysis of the V-band data reveals the period estimations of 51.2±2.8 years and 15.1±0.7 years superposed on it. The U-B, B-V and V-R colors do not show correlation with the longer period, but they show variations with a period similar to the shorter one, except for B-V color. The amplitude variation also does not exhibit any correlation with the V light and color curves. It is found that the movement of the spot minima phases in years also indicates the migration period of nearly 15 years, similar to the period derived from the analysis of the long-term photometric observations in V-band.

The long-term instability of the new generation hydrogen masers

2020 ◽  
pp. 35-38
Author(s):  
S.I. Donchenko ◽  
I.Y. Blinov ◽  
I.B. Norets ◽  
Y.F. Smirnov ◽  
A.A. Belyaev ◽  
...  
Keyword(s):  
Time Scale ◽  
Frequency Difference ◽  
Clock Frequency ◽  
Quantum Frequency ◽  
Frequency Standards ◽  
Quantum Frequency Standards ◽  
New Generation ◽  
Atomic Time

The latest changes in the algorithm for the formation of the international atomic time scale TAI are reported in terms of estimating the weights of the clocks involved in the formation of TAI. Studies of the characteristics of the long-term instability of new-generation hydrogen masers based on processing the results of the clock frequency difference with respect to TAI are performed. It has been confirmed that at present, new-generation hydrogen masers show significantly less long-term instability in comparison with quantum frequency standards ofsimilar and other types.

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

Rheumatology ◽  
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.

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

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.

Sensor-Based Estimation of Dim Light Melatonin Onset Using Features of Two Time Scales

2021 ◽  
Vol 2 (3) ◽  
pp. 1-15
Author(s):  
Cheng Wan ◽  
Andrew W. Mchill ◽  
Elizabeth B. Klerman ◽  
Akane Sano
Keyword(s):  
Time Scales ◽  
Time Scale ◽  
Light Exposure ◽  
Biological Activities ◽  
Second Step ◽  
Sampled Data ◽  
Dim Light Melatonin Onset ◽  
Dim Light ◽  
Using Data ◽  
Mean Square Errors

Circadian rhythms influence multiple essential biological activities, including sleep, performance, and mood. The dim light melatonin onset (DLMO) is the gold standard for measuring human circadian phase (i.e., timing). The collection of DLMO is expensive and time consuming since multiple saliva or blood samples are required overnight in special conditions, and the samples must then be assayed for melatonin. Recently, several computational approaches have been designed for estimating DLMO. These methods collect daily sampled data (e.g., sleep onset/offset times) or frequently sampled data (e.g., light exposure/skin temperature/physical activity collected every minute) to train learning models for estimating DLMO. One limitation of these studies is that they only leverage one time-scale data. We propose a two-step framework for estimating DLMO using data from both time scales. The first step summarizes data from before the current day, whereas the second step combines this summary with frequently sampled data of the current day. We evaluate three moving average models that input sleep timing data as the first step and use recurrent neural network models as the second step. The results using data from 207 undergraduates show that our two-step model with two time-scale features has statistically significantly lower root-mean-square errors than models that use either daily sampled data or frequently sampled data.

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

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.

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

2020 ◽  
Vol 13 ◽  
pp. 175628642092268 ◽  
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.

Solid–liquid–liquid phase envelopes from temperature-scanned refractive index data

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Alcides J. Sitoe ◽  
Franco Pretorius ◽  
Walter W. Focke ◽  
René Androsch ◽  
Elizabeth L. du Toit
Keyword(s):  
Refractive Index ◽  
Liquid Phase ◽  
Volume Fraction ◽  
Solution Temperature ◽  
Linear Behavior ◽  
Upper Critical Solution Temperature ◽  
Novel Method ◽  
Using Data ◽  
Solid Liquid ◽  
Liquid Liquid Phase Separation

Abstract A novel method for estimating the upper critical solution temperature (UCST) of N,N-diethyl-m-toluamide (DEET)-polyethylene systems was developed. It was validated using data for the dimethylacetamide (DMA)-alkane systems which showed that refractive index mixing rules, linear in volume fraction, can accurately predict mixture composition for amide-alkane systems. Furthermore, rescaling the composition descriptor with a single adjustable parameter proved adequate to address any asymmetry when modeling the DMA-alkane phase envelopes. This allowed the translation of measured refractive index cooling trajectories of DEET-alkane systems into phase diagrams and facilitated the estimation of the UCST values by fitting the data with an adjusted composition descriptor model. For both the DEET- and DMA-alkane systems, linear behavior of UCST values in either the Flory–Huggins critical interaction parameter, or the alkane critical temperature, with increasing alkane molar mass is evident. The UCST values for polymer diluent systems were estimated by extrapolation using these two complimentary approaches. For the DEET-polyethylene system, values of 183.4 and 180.1 °C respectively were obtained. Both estimates are significantly higher than the melting temperature range of polyethylene. Initial liquid–liquid phase separation is therefore likely to be responsible for the previously reported microporous microstructure of materials formed from this binary system.

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

Cancers ◽  
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.

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

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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