A statistical modeling method for estimating mortality and abundance of spawning salmon from a time series of counts

2008 ◽  
Vol 65 (1) ◽  
pp. 17-26 ◽  
Author(s):  
R Glenn Szerlong ◽  
David E Rundio
Keyword(s):  
Time Series ◽  
Statistical Modeling ◽  
Detection Rate ◽  
Coho Salmon ◽  
Modeling Method ◽  
Detection Rates ◽  
Abundance Estimate ◽  
Mortality Model ◽  
Abundance Estimates ◽  
Approximate Likelihood

We present a statistical modeling method for estimating mortality and abundance of spawning salmon from time-series counts that eliminates the need for separate information about mortality. We model arrival and mortality using differential equations, where mortality can be constant or changing linearly, and estimate mortality and abundance from counts using maximum likelihood when multiple estimates of detection rate are available. We also develop an approximate likelihood to estimate mortality and abundance when only a single value for detection rate is available or to estimate only mortality when detection rates are entirely unknown. We demonstrate our approach using counts of coho salmon (Oncorhynchus kisutch) where mortality, abundance, and detection were determined from tagging at a weir. Our model for nonconstant mortality produced mortality estimates that closely matched the empirical data and were robust to variation in other parameters. It also provided a better fit to the stream counts and a closer abundance estimate to the weir count than the constant mortality model. Monte Carlo simulations indicated that the approximate likelihood provided reasonable estimates of mortality over most of the ranges of parameters explored, particularly under the nonconstant mortality model, and produced relatively unbiased abundance estimates using a single value for detection.

EVALUATION OF THE RELIABILITY OF COMPLEX TECHNICAL RECONFIGURATION SYSTEMS BY STATISTICAL MODELING METHOD

2019 ◽  
pp. 84-88
Author(s):  
A.Yu. Kulakov
Keyword(s):  
Normal Distribution ◽  
Statistical Modeling ◽  
Quantitative Estimate ◽  
Failure Time ◽  
Modeling Method ◽  
System Failure ◽  
Similar System ◽  
Orbit Control ◽  
Reliability Characteristics ◽  
Complex Technical System

Goal. Assess the reliability of a complex technical system with periodic reconfiguration and compare the results obtained a similar system, but without reconfiguration. Materials and methods. In this article uses the method of statistical modeling (Monte Carlo) to assess the reliability of complex system. We using the normal and exponential distribution of failure time for modeling failures of system elements. Reconfiguration algorithm is the algorithm proposed for the attitude and orbit control system of spacecraft. Results. A computer program has been developed for assessing reliability on the basis of a statistical modeling method, which makes it possible to evaluate systems of varying complexity with exponential and normal distribution, as well as with and without periodic reconfiguration. A quantitative estimate of the reliability as a function of the probability of system failure is obtained. Conclusion. It has been demonstrated that a system with reconfiguration has the best reliability characteristics, both in the case of exponential and normal distribution of failures.

scholarly journals Training: improving antenatal detection and outcomes of congenital heart disease

2018 ◽  
Vol 7 (4) ◽  
pp. e000276 ◽  
Author(s):  
Orhan Uzun ◽  
Julia Kennedy ◽  
Colin Davies ◽  
Anthony Goodwin ◽  
Nerys Thomas ◽  
...  
Keyword(s):  
Congenital Heart Disease ◽  
Detection Rate ◽  
Congenital Heart ◽  
Training Programme ◽  
Referral Rate ◽  
Cardiac Anomaly ◽  
Cardiac Ultrasound ◽  
Detection Rates ◽  
Antenatal Detection ◽  
The Uk

ObjectivesThis study describes the design, delivery and efficacy of a regional fetal cardiac ultrasound training programme. This programme aimed to improve the antenatal detection of congenital heart disease (CHD) and its effect on fetal and postnatal outcomes.Design setting and participantsThis was a prospective study that compared antenatal CHD detection rates by professionals from 13 hospitals in Wales before and after engaging in our ‘skills development programme’. Existing fetal cardiac practice and perinatal outcomes were continuously audited and progressive targets were set. The work was undertaken by the Welsh Fetal Cardiovascular Network, Antenatal Screening Wales (ASW), a superintendent sonographer and a fetal cardiologist.InterventionsA core professional network was established, engaging all stakeholders (including patients, health boards, specialist commissioners, ASW, ultrasonographers, radiologists, obstetricians, midwives and paediatricians). A cardiac educational lead (midwife, superintendent sonographer, radiologist, obstetrician, or a fetal medicine specialist) was established in each hospital. A new cardiac anomaly screening protocol (‘outflow tract view’) was created and training on the new protocol was systematically delivered at each centre. Data were prospectively collected and outcomes were continuously audited: locally by the lead fetal cardiologist; regionally by the Congenital Anomaly Register and Information Service in Wales; and nationally by the National Institute for Cardiac Outcomes and Research (NICOR) in the UK.Main outcome measuresPatient satisfaction; improvements in individual sonographer skills, confidence and competency; true positive referral rate; local hospital detection rate; national detection rate of CHD; clinical outcomes of selected cardiac abnormalities; reduction of geographical health inequality; cost efficacy.ResultsHigh levels of patient satisfaction were demonstrated and the professional skill mix in each centre was improved. The confidence and competency of sonographers was enhanced. Each centre demonstrated a reduction in the false-positive referral rate and a significant increase in cardiac anomaly detection rate. According to the latest NICOR data, since implementing the new training programme Wales has sustained its status as UK lead for CHD detection. Health outcomes of children with CHD have improved, especially in cases of transposition of the great arteries (for which no perinatal mortality has been reported since 2008). Standardised care led to reduction of geographical health inequalities with substantial cost saving to the National Health Service due to reduced false-positive referral rates. Our successful model has been adopted by other fetal anomaly screening programmes in the UK.ConclusionsAntenatal cardiac ultrasound mass training programmes can be delivered effectively with minimal impact on finite healthcare resources. Sustainably high CHD detection rates can only be achieved by empowering the regional screening workforce through continuous investment in lifelong learning activities. These should be underpinned by high quality service standards, effective care pathways, and robust clinical governance and audit practices.

scholarly journals Mortality due to primary brain tumours in China and detection rate in people with suspected symptoms: a nationally representative cross-sectional survey

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Bin Jiang ◽  
Hongmei Liu ◽  
Dongling Sun ◽  
Haixin Sun ◽  
Xiaojuan Ru ◽  
...  
Keyword(s):  
Brain Tumour ◽  
Brain Tumours ◽  
Detection Rate ◽  
Epidemiological Data ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Detection Rates ◽  
Primary Brain Tumours ◽  
Symptom Screening ◽  
Nationally Representative

Abstract Background and purpose Epidemiological data on primary brain tumours (PBTs) are lacking due to the difficulty in case ascertainment among the population. Thus, we aimed to estimate mortality due to PBTs in China nationwide and the detection rate in people with suspected symptoms. Methods A multistage, complex sampling survey regarding mortality due to PBTs in Chinese individuals was carried out by reviewing all causes of death within a year. The detection rates in people with suspected symptoms were estimated based on PBT symptom screening and neurologist reviews and compared between groups by logistic regression analysis. Results Weighted mortality due to PBT was 1.6 (0.8–3.3) per 100,000 population in Chinese individuals, 1.8 (0.7–4.6) per 100,000 population in men, and 1.5 (0.5–4.5) per 100,000 population in women. Among 14,990 people with suspected symptoms, the PBT detection rate was 306.9 (95% CI 224.7–409.3) per 100,000 population in the total population, 233.0 (95% CI 135.7–373.1) per 100,000 population in men, and 376.9 (95% CI 252.4–546.3) per 100,000 population in women. People with an unsteady gait (OR 2.46; 95% CI 1.09–5.51; P=0.029), visual anomalies (3.84; 1.88–7.85; P<0.001), and headache (2.06; 1.10–3.86; P=0.023) were more likely to have a brain tumour than those without corresponding symptoms, while people with dizziness/vertigo were less likely to have a brain tumour than those without corresponding symptoms (0.45; 0.23–0.87; P=0.017). Conclusions Mortality due to PBT in China was low, with a nationwide estimate of 21,215 (10,427–43,165) deaths attributable to PBTs annually. However, the detection rate of PBTs can be greatly improved based on symptom screening in the population.

scholarly journals An Energy-Based Discrete Element Modeling Method Coupled with Time-Series Analysis for Investigating Deformations and Failures of Jointed Rock Slopes

2021 ◽  
Vol 11 (12) ◽  
pp. 5447
Author(s):  
Xiaona Zhang ◽  
Gang Mei ◽  
Ning Xi ◽  
Ziyang Liu ◽  
Ruoshen Lin
Keyword(s):  
Time Series ◽  
Iterative Process ◽  
Discrete Element ◽  
Jointed Rock ◽  
Modeling Method ◽  
Discrete Element Modeling ◽  
Rock Slopes ◽  
Sliding Surface ◽  
Element Modeling ◽  
Displacement Based

The discrete element method (DEM) can be effectively used in investigations of the deformations and failures of jointed rock slopes. However, when to appropriately terminate the DEM iterative process is not clear. Recently, a displacement-based discrete element modeling method for jointed rock slopes was proposed to determine when the DEM iterative process is terminated, and it considers displacements that come from rock blocks located near the potential sliding surface that needs to be determined before the DEM modeling. In this paper, an energy-based discrete element modeling method combined with time-series analysis is proposed to investigate the deformations and failures of jointed rock slopes. The proposed method defines an energy-based criterion to determine when to terminate the DEM iterative process in analyzing the deformations and failures of jointed rock slopes. The novelty of the proposed energy-based method is that, it is more applicable than the displacement-based method because it does not need to determine the position of the potential sliding surface before DEM modeling. The proposed energy-based method is a generalized form of the displacement-based discrete element modeling method, and the proposed method considers not only the displacement of each block but also the weight of each block. Moreover, the computational cost of the proposed method is approximately the same as that of the displacement-based discrete element modeling method. To validate that the proposed energy-based method is effective, the proposed method is used to analyze a simple jointed rock slope; the result is compared to that achieved by using the displacement-based method, and the comparative results are basically consistent. The proposed energy-based method can be commonly used to analyze the deformations and failures of general rock slopes where it is difficult to determine the obvious potential sliding surface.

scholarly journals The Effects of Social Distancing Policies on non-SARS-CoV-2 Respiratory Pathogens

2021 ◽  
Author(s):  
Jeff Nawrocki ◽  
Katherine Olin ◽  
Martin C Holdrege ◽  
Joel Hartsell ◽  
Lindsay Meyers ◽  
...  
Keyword(s):  
Public Health ◽  
Influenza A ◽  
Detection Rate ◽  
Respiratory Illness ◽  
Respiratory Pathogens ◽  
Public Health Response ◽  
Mixed Effect ◽  
Detection Rates ◽  
Social Distancing ◽  
The Impact

Abstract Background The initial focus of the US public health response to COVID-19 was the implementation of numerous social distancing policies. While COVID-19 was the impetus for imposing these policies, it is not the only respiratory disease affected by their implementation. This study aimed to assess the impact of social distancing policies on non-SARS-CoV-2 respiratory pathogens typically circulating across multiple US states. Methods Linear mixed-effect models were implemented to explore the effects of five social distancing policies on non-SARS-CoV-2 respiratory pathogens across nine states from January 1 through May 1, 2020. The observed 2020 pathogen detection rates were compared week-by-week to historical rates to determine when the detection rates were different. Results Model results indicate that several social distancing policies were associated with a reduction in total detection rate, by nearly 15%. Policies were associated with decreases in pathogen circulation of human rhinovirus/enterovirus and human metapneumovirus, as well as influenza A, which typically decrease after winter. Parainfluenza viruses failed to circulate at historical levels during the spring. Total detection rate in April 2020 was 35% less than historical average. Many of the pathogens driving this difference fell below historical detection rate ranges within two weeks of initial policy implementation. Conclusion This analysis investigated the effect of multiple social distancing policies implemented to reduce transmission of SARS-CoV-2 on non-SARS-CoV-2 respiratory pathogens. These findings suggest that social distancing policies may be used as an impactful public health tool to reduce communicable respiratory illness.

scholarly journals Comparison of colonoscopy after colonic diverticulitis and positive fecal immunochemical tests for the detection of colorectal neoplasia

2021 ◽  
Vol 09 (03) ◽  
pp. E331-E337
Author(s):  
Dai Nakamatsu ◽  
Tsutomu Nishida ◽  
Shinji Kuriki ◽  
Li-sa Chang ◽  
Kazuki Aochi ◽  
...  
Keyword(s):  
Detection Rate ◽  
Colorectal Neoplasia ◽  
Acute Diverticulitis ◽  
Colonic Diverticulitis ◽  
Detection Rates ◽  
Positive Group ◽  
Asymptomatic Patients ◽  
Polyp Detection Rate ◽  
Adenoma Detection ◽  
Acute Colonic Diverticulitis

Abstract Background and study aims The relationship between acute colonic diverticulitis and colorectal cancer (CRC) is unclear, but colonoscopy is recommended to exclude malignancy. We compared the detection rates for colorectal neoplasia in patients with colonic diverticulitis and asymptomatic patients who had positive fecal immunochemical tests (FITs). Patients and methods In total, 282 patients with acute colonic diverticulitis were hospitalized in our hospital from February 2011 to December 2019. Of them, 143 patients with diverticulitis and 1819 with positive FITs patients during the same period underwent colonoscopy without a prior colonoscopy within 5 years. We retrospectively compared these patients in terms of the invasive CRC rate, advanced neoplasia detection rate (ANDR), adenoma detection rate (ADR), and polyp detection rate (PDR). Results Compared to the diverticulitis group, the FIT-positive group had a significantly higher CRC rate (0 vs 2.7 %, P = 0.0061), ANDR (5.6 vs. 14.0 %, P = 0.0017), ADR (19.6 vs. 53.2 %, P < .0001), and PDR (44.1 vs. 91.0 %, P < .0001). Using 1:1 propensity score matching based on age and sex, we obtained 276 matched patients in both groups. After matching, no difference was found in the CRC rate (0 vs 0.7 %) or ANDR (5.8 vs 7.3 %) between groups, but the ADR and PDR were significantly higher in the FIT-positive group (20.3 vs 43.5 %, P < .0001; 45.7 % vs 86.2 %, P < .0001). Conclusion Patients with acute diverticulitis had lower ADRs and PDRs than patients with positive FITs.

scholarly journals Night-Time Vehicle Sensing in Far Infrared Image with Deep Learning

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Hai Wang ◽  
Yingfeng Cai ◽  
Xiaobo Chen ◽  
Long Chen
Keyword(s):  
Detection Rate ◽  
False Positive Rate ◽  
Infrared Image ◽  
Far Infrared ◽  
Night Vision ◽  
Infrared Sensors ◽  
Night Time ◽  
Detection Rates ◽  
Positive Rate ◽  
And Performance

The use of night vision systems in vehicles is becoming increasingly common. Several approaches using infrared sensors have been proposed in the literature to detect vehicles in far infrared (FIR) images. However, these systems still have low vehicle detection rates and performance could be improved. This paper presents a novel method to detect vehicles using a far infrared automotive sensor. Firstly, vehicle candidates are generated using a constant threshold from the infrared frame. Contours are then generated by using a local adaptive threshold based on maximum distance, which decreases the number of processing regions for classification and reduces the false positive rate. Finally, vehicle candidates are verified using a deep belief network (DBN) based classifier. The detection rate is 93.9% which is achieved on a database of 5000 images and video streams. This result is approximately a 2.5% improvement on previously reported methods and the false detection rate is also the lowest among them.

Time series analysis and mortality model of dog bite victims presented for treatment at a referral clinic for rabies exposure in Monrovia, Liberia, 2010–2013

2017 ◽  
Vol 22 ◽  
pp. 1-13 ◽  
Author(s):  
Ayodeji O. Olarinmoye ◽  
Johnson F. Ojo ◽  
Ayotunde J. Fasunla ◽  
Olayinka O. Ishola ◽  
Fahnboah G. Dakinah ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Dog Bite ◽  
Mortality Model ◽  
Series Analysis ◽  
Rabies Exposure
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