A logistic function to track time-dependent fish population dynamics

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Monitoring of fisheries resources in artificial reefs in east of Kish Island waters

Artificial reefs are manmade materials deployed under water in order to improve environment and increase the exploitation of fishing area. Usage of artificial technic has developed due to increase of world population and need to supply of protein, aim to restoring of natural specially rehabilitation of demersal fishes. It has effected to increase the production in order sustainable exploitation. Coasts and Islands have destruction due to over harvesting from ecosystems and other activities by humans and natural, these caused many aquatic as demersal fishes has endangered in Persian Gulf and Oman Sea. The artificial reef is one way or method that can improve the environment and restore the aquatic. Iranian fisheries has established an artificial reefs area in west of Kish Island. This area has studied during one year, Data of assembled fishes and physical sampling were collected in seasonal during spring, summer, autumn and wintered. There were tow treatment for sampling as artificial reefs site and a control site. Collected data has analyzed and evaluated by SPSS and Exel. The results showed that there was significant difference between the sites and assembled fishes in artificial reefs were more than control site. Consequently the artificial reefs can be a tool and technic to improve the marine environment and increase the production of fishes, especially the demersal fishes

Epidemiological study on some environmental and management parameters affecting on WSD occurrence in Fenneropenaeus indicus and Penaeus vannamei

For the first time white spot disease (WSD) was reported in shrimp farms of khoozestan province, in southwest of IRAN in 2002. Then in 2005 the neighbor province, boushehr, was contaminated. In 2008 WSD outbreak reported in sistan-bloochestan province in southeast of Iran. In 2015 all of southern shrimp farms of country except Hormozgan, the middle southern province, which has remained free of WSD, are being contaminated. White Spot disease suspended shrimp culture in thousands hectares of shrimp farms. Considering that white spot disease has not been observed in Hormozgan province yet, the question is; to what extent environmental and management factors participated in preventing WSD outbreak or cause WSD outbreak. In this study (20102012), the effects of environmental factors and management, stressors that decrease immune system function of shrimp are discussed. In addition, the role of pathogen as the main factor of outbreak is discussed. The goal of this study is to define environmental parameters and management practices associates with outbreak of white spot disease in affected provinces and discover reasons of being Hormozgan province free of this disease. In this study the role of the local environmental factors and management practice stressors in susceptibility to WSD was determine. Both the effects of environmental factors in water of ponds including total ammonia, nitrogen, dissolved oxygen, pH, salinity, transparency, and temperature and management issues related to biosecurity are studied. There were overlaps on physical and chemical parameter values obtained in clear areas with contaminated areas .Results of the data analysis suggest that lack of association with WSD incidence was 7 times greater than WSD incidence despite of disease outbreak in sistan-bloochestan province, so other sources of white spot disease virus incidence was suspected in affected areas. Histopathological examinations and polymerase chain reaction (PCR) tests during project performance did not reveal white spot disease virus evidences in post larvae examined from khoozestan province stocked in farms but disease outbreak was happened in that farms , so we suspected to management practice include feed , pond preparation and carrier of disease. Recorded values of temperature and salinity in some months during inspection in Hormozgan province specified stressful condition that may lead to WSD outbreak, however the disease did not appear. Therefore the hypothesis that the water physical and chemical conditions are reasons to prevent disease outbreak in Hormozgan province is being rejected. The policy of Hormozgan’s fishery authorities, to replaced Fenneropenaeus indicus with specific pathogen free Litopenaeus vannamei, that is more resistant to some of diseases, before incidence of WSD in farms and to before being endemic in the Hormozgan province, made an advantage compare to affected southern provinces that introduced Litopenaeus vannamei after WSD prevalence to their farms. However it does not guarantee to maintain current trend of being Hormozgan province farms free of white spot disease. Therefore establishing the principals of biosecurity are strongly emphasized. Strategies taken by the proficient authorities in preparation of SPF shrimp broodstock can be the most important factor in preventing WSD. Regarding biosecurity principals purchased feed must be free of shrimp head powder. Construction the new shrimp farms should be as far as it could be away from contaminated areas

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

Numerical solution of second order one-dimensional linear hyperbolic equation using trigonometric wavelets

summary:A numerical technique is presented for the solution of second order one dimensional linear hyperbolic equation. This method uses the trigonometric wavelets. The method consists of expanding the required approximate solution as the elements of trigonometric wavelets. Using the operational matrix of derivative, we reduce the problem to a set of algebraic linear equations. Some numerical example is included to demonstrate the validity and applicability of the technique. The method produces very accurate results. An estimation of error bound for this method is presented and it is shown that in this method the matrix of coefficients is a sparse matrix

A logistic function to track time-dependent fish population dynamics

This paper uses a two-parameter logistic function to model the dynamics of length-at-maturation for the Barents Sea capelin over the past 47 years. We estimate the function parameters using a combination of length-age data from scientific surveys, and commercial catch statistics. Using temporal variability in the function parameters, we demonstrate that the time series of stock biomass defines a three-state Markov process, that qualitatively represent high, moderate, and collapse states of the stock biomass. We make inference about transition times between the states by calculating the mean passage times for the Markov process. Our analyses also show that maturation intensity is higher at low stock size (leading to shorter lengths at maturation), compared to when biomass levels are either high or moderately high. Our results are central to management of this stock, as uncertainty in estimating the proportion of maturing biomass affects harvest decisions and ultimately, the sustainability of the stock

Computation of Half-eigenvalues Periodic Sturm-Liouville Problem Using Trigonometric Wavelets

Abstract: The main aim of this paper is to apply the trigonometric wavelets for the computation of eigenvalues and eigenfunctions of Sturm-Liouville problem. The operational matrices of derivative for Trigonometric scaling functions and wavelets are presented and utilized to reduce the solution of the problem to find the eigenvalues of a matrix

COMPARATIVE STUDY OF COMPLETED SUICIDE BASED ON SEASON AND DISEASES IN BUSHEHR PROVINCE, (2006-2015)

Suicide, an act in which individuals sacrifice voluntarily themselves, is considered as a serious psychosocial problem. The main objective of the present study was to determine the comparative study of completed suicide based on season and diseases in Bushehr during 2006-2015. This consideration has been done as a retrospective cross-sectional study; the data were collected by the check list. After coordination to the medico legal 343 cases of completed suicide lead to death over a ten year period from 2006 to 2015 were extracted and the data were analyses by SPSS software. Completed suicides were most prevalent in spring 29.7% (102), whereas least prevalent in autumn 20.1% (69). There was no significantly in different seasons in year (P=0.065). But, was a statistically significant difference observed in the different gender and different seasons of the year (P=0.001). The maximum number of completed suicides 10.2% (35) was observed in April, while the minimum number 6.1% (21) was reported in September and October, too. The value Chi square test was statistically significant differences diseases and different seasons (P=0. 001). The psychological disease was observed most in spring and winter seasons. Also was a significant relationship between season of the year and the method of suicide (P=0.001). The number of completed suicides was higher in moderate and cold season