Gasoline Demand, Pricing Policy and Social Welfare in Iran

This study estimates a gasoline demand function for Iran using the structural time series model over the period 1968-2002 and uses it to estimate the change in social welfare for 2003 and 2004 of a higher gasoline price policy. It is found that short and long run demand price elasticities are inelastic, although the response is greater in the long run. Hence, social welfare is estimated to fall because of the higher gasoline price (ceteris paribus). However, allowing all variables in the model to change, social welfare is estimated to increase since the changes in the other variables more than compensate for the negative effects of the policy.

Heterogeneous Graph Learning for Acoustic Event Classification

Heterogeneous graphs provide a compact, efficient, and scalable way to model data involving multiple disparate modalities. This makes modeling audiovisual data using heterogeneous graphs an attractive option. However, graph structure does not appear naturally in audiovisual data. Graphs for audiovisual data are constructed manually which is both difficult and sub-optimal. In this work, we address this problem by (i) proposing a parametric graph construction strategy for the intra-modal edges, and (ii) learning the crossmodal edges. To this end, we develop a new model, heterogeneous graph crossmodal network (HGCN) that learns the crossmodal edges. Our proposed model can adapt to various spatial and temporal scales owing to its parametric construction, while the learnable crossmodal edges effectively connect the relevant nodes across modalities. Experiments on a large benchmark dataset (AudioSet) show that our model is state-of-the-art (0.53 mean average precision), outperforming transformer-based models and other graph-based models.Comment: arXiv admin note: text overlap with arXiv:2207.0793

In Vitro Comparative Study on Antineoplastic Effects of Pinoresinol and Lariciresinol on Healthy Cells and Breast Cancer-Derived Human Cells

Background: Herbal medicines are the preferred anticancer agents due to their lower cytotoxic effects on healthy cells. Plant lignans play an important role in treating various diseases, especially cancer. The present study aimed to evaluate the effect of podophyllotoxin, pinoresinol, and lariciresinol on cellular toxicity and inducing apoptosis in fibroblasts, HEK-293, and SkBr3 cell lines.Methods: An in vitro study was conducted from 2017 to 2019 at the Faculty of Biological Sciences, Tarbiat Modares University (Tehran, Iran). The cell lines were treated for 24 and 48 hours with different concentrations of lignans. Cell viability and apoptosis were examined using MTT and flow cytometry, respectively. Expression levels of cell cycle and apoptosis regulator genes were determined using quantitative real-time polymerase chain reaction. Data were analyzed using a two-way analysis of variance followed by Tukey’s HSD test. P<0.05 was considered statistically significant.Results: Podophyllotoxin significantly increased apoptosis in fibroblast cells compared to pinoresinol and lariciresinol (P<0.001). The percentage of cell viability of fibroblast cells treated for 48 hours with pinoresinol, lariciresinol, and podophyllotoxin was reduced by 49%, 47%, and 36%, respectively. Treatment with pinoresinol and lariciresinol significantly overexpressed pro-apoptotic genes and underexpressed anti-apoptotic genes in SkBr3 cells (P<0.001). SkBr3 cells treated with lariciresinol significantly reduced gene expression (P<0.001). Conclusion: Pinoresinol and lariciresinol can potentially be used as new therapeutic agents for the treatment of breast cancer

Global, regional, and national burden of chronic kidney disease, 1990–2017 : a systematic analysis for the Global Burden of Disease Study 2017

Background Health system planning requires careful assessment of chronic kidney disease (CKD) epidemiology, but data for morbidity and mortality of this disease are scarce or non-existent in many countries. We estimated the global, regional, and national burden of CKD, as well as the burden of cardiovascular disease and gout attributable to impaired kidney function, for the Global Burden of Diseases, Injuries, and Risk Factors Study 2017. We use the term CKD to refer to the morbidity and mortality that can be directly attributed to all stages of CKD, and we use the term impaired kidney function to refer to the additional risk of CKD from cardiovascular disease and gout. Methods The main data sources we used were published literature, vital registration systems, end-stage kidney disease registries, and household surveys. Estimates of CKD burden were produced using a Cause of Death Ensemble model and a Bayesian meta-regression analytical tool, and included incidence, prevalence, years lived with disability, mortality, years of life lost, and disability-adjusted life-years (DALYs). A comparative risk assessment approach was used to estimate the proportion of cardiovascular diseases and gout burden attributable to impaired kidney function. Findings Globally, in 2017, 1·2 million (95% uncertainty interval [UI] 1·2 to 1·3) people died from CKD. The global all-age mortality rate from CKD increased 41·5% (95% UI 35·2 to 46·5) between 1990 and 2017, although there was no significant change in the age-standardised mortality rate (2·8%, −1·5 to 6·3). In 2017, 697·5 million (95% UI 649·2 to 752·0) cases of all-stage CKD were recorded, for a global prevalence of 9·1% (8·5 to 9·8). The global all-age prevalence of CKD increased 29·3% (95% UI 26·4 to 32·6) since 1990, whereas the age-standardised prevalence remained stable (1·2%, −1·1 to 3·5). CKD resulted in 35·8 million (95% UI 33·7 to 38·0) DALYs in 2017, with diabetic nephropathy accounting for almost a third of DALYs. Most of the burden of CKD was concentrated in the three lowest quintiles of Socio-demographic Index (SDI). In several regions, particularly Oceania, sub-Saharan Africa, and Latin America, the burden of CKD was much higher than expected for the level of development, whereas the disease burden in western, eastern, and central sub-Saharan Africa, east Asia, south Asia, central and eastern Europe, Australasia, and western Europe was lower than expected. 1·4 million (95% UI 1·2 to 1·6) cardiovascular disease-related deaths and 25·3 million (22·2 to 28·9) cardiovascular disease DALYs were attributable to impaired kidney function. Interpretation Kidney disease has a major effect on global health, both as a direct cause of global morbidity and mortality and as an important risk factor for cardiovascular disease. CKD is largely preventable and treatable and deserves greater attention in global health policy decision making, particularly in locations with low and middle SDI

The global, regional, and national burden of cirrhosis by cause in 195 countries and territories, 1990-2017 : a systematic analysis for the Global Burden of Disease Study 2017

Background Cirrhosis and other chronic liver diseases (collectively referred to as cirrhosis in this paper) are a major cause of morbidity and mortality globally, although the burden and underlying causes differ across locations and demographic groups. We report on results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 on the burden of cirrhosis and its trends since 1990, by cause, sex, and age, for 195 countries and territories. Methods We used data from vital registrations, vital registration samples, and verbal autopsies to estimate mortality. We modelled prevalence of total, compensated, and decompensated cirrhosis on the basis of hospital and claims data. Disability-adjusted life-years (DALYs) were calculated as the sum of years of life lost due to premature death and years lived with disability. Estimates are presented as numbers and age-standardised or age-specific rates per 100 000 population, with 95% uncertainty intervals (UIs). All estimates are presented for five causes of cirrhosis: hepatitis B, hepatitis C, alcohol-related liver disease, non-alcoholic steatohepatitis (NASH), and other causes. We compared mortality, prevalence, and DALY estimates with those expected according to the Socio-demographic Index (SDI) as a proxy for the development status of regions and countries. Findings In 2017, cirrhosis caused more than 1.32 million (95% UI 1.27-1.45) deaths (440000 [416 000-518 000; 33.3%] in females and 883 000 [838 000-967 000; 66.7%] in males) globally, compared with less than 899 000 (829 000-948 000) deaths in 1990. Deaths due to cirrhosis constituted 2.4% (2.3-2.6) of total deaths globally in 2017 compared with 1.9% (1.8-2.0) in 1990. Despite an increase in the number of deaths, the age-standardised death rate decreased from 21.0 (19.2-22.3) per 100 000 population in 1990 to 16.5 (15.8-18-1) per 100 000 population in 2017. Sub-Saharan Africa had the highest age-standardised death rate among GBD super-regions for all years of the study period (32.2 [25.8-38.6] deaths per 100 000 population in 2017), and the high-income super-region had the lowest (10.1 [9.8-10-5] deaths per 100 000 population in 2017). The age-standardised death rate decreased or remained constant from 1990 to 2017 in all GBD regions except eastern Europe and central Asia, where the age-standardised death rate increased, primarily due to increases in alcohol-related liver disease prevalence. At the national level, the age-standardised death rate of cirrhosis was lowest in Singapore in 2017 (3.7 [3.3-4.0] per 100 000 in 2017) and highest in Egypt in all years since 1990 (103.3 [64.4-133.4] per 100 000 in 2017). There were 10.6 million (10.3-10.9) prevalent cases of decompensated cirrhosis and 112 million (107-119) prevalent cases of compensated cirrhosis globally in 2017. There was a significant increase in age-standardised prevalence rate of decompensated cirrhosis between 1990 and 2017. Cirrhosis caused by NASH had a steady age-standardised death rate throughout the study period, whereas the other four causes showed declines in age-standardised death rate. The age-standardised prevalence of compensated and decompensated cirrhosis due to NASH increased more than for any other cause of cirrhosis (by 33.2% for compensated cirrhosis and 54.8% for decompensated cirrhosis) over the study period. From 1990 to 2017, the number of prevalent cases snore than doubled for compensated cirrhosis due to NASH and more than tripled for decompensated cirrhosis due to NASH. In 2017, age-standardised death and DALY rates were lower among countries and territories with higher SDI. Interpretation Cirrhosis imposes a substantial health burden on many countries and this burden has increased at the global level since 1990, partly due to population growth and ageing. Although the age-standardised death and DALY rates of cirrhosis decreased from 1990 to 2017, numbers of deaths and DALYs and the proportion of all global deaths due to cirrhosis increased. Despite the availability of effective interventions for the prevention and treatment of hepatitis B and C, they were still the main causes of cirrhosis burden worldwide, particularly in low-income countries. The impact of hepatitis B and C is expected to be attenuated and overtaken by that of NASH in the near future. Cost-effective interventions are required to continue the prevention and treatment of viral hepatitis, and to achieve early diagnosis and prevention of cirrhosis due to alcohol-related liver disease and NASH. Copyright (C) 2020 The Author(s). Published by Elsevier Ltd.Peer reviewe

Gasoline demand, pricing policy and social welfare in the Islamic Republic of Iran

This study estimates the gasoline demand function for the Islamic Republic of Iran, using the structural time series model over the period 1968-2002, and uses it to estimate the change in social welfare for 2003 and 2004, of a higher gasoline price policy. It is found that short- and long-run demand price elasticities are inelastic, although the response is greater in the long run. Hence, social welfare is estimated to fall because of the higher gasoline price (ceteris paribus). However, allowing all variables in the model to change, social welfare is estimated to increase since the changes in the other variables more than compensate for the negative effects of the policy. Copyright 2007 Organization of the Petroleum Exporting Countries.

Future image prediction of plantar pressure during gait using spatio-temporal transformer

Gait is one of the most frequently used forms of human movement during daily activities. The majority of works focus on exploring the dynamic factors during gait. Different from previous works, we adapt an image prediction task for anticipating the next frame in process of gait. In this work, we present a novel framework for human gait plantar pressure prediction using Spatio-temporal Transformer. We train the model to predict the next plantar pressure image in an image series while also learning frame feature encoders that predict the features of subsequent frames in the sequence. We proposed two new components in our loss function for considering temporality as well as smaller values in the image. Our model achieves superior results over several competitive baselines on the CAD WALK database. Clinical Relevance— This work can be used in robotic exoskeleton devices which are intelligent systems designed to improve gait performance and quality of life for the wearer that are being used to assist the recovery of walking ability for patients with disorders

Heterogeneous Graph Learning for Acoustic Event Classification

Heterogeneous graphs provide a compact, efficient, and scalable way to model data involving multiple disparate modalities. This makes modeling audiovisual data using heterogeneous graphs an attractive option. However, graph structure does not appear naturally in audiovisual data. Graphs for audiovisual data are constructed manually which is both difficult and sub-optimal. In this work, we address this problem by (i) proposing a parametric graph construction strategy for the intra-modal edges, and (ii) learning the crossmodal edges. To this end, we develop a new model, heterogeneous graph crossmodal network (HGCN) that learns the crossmodal edges. Our proposed model can adapt to various spatial and temporal scales owing to its parametric construction, while the learnable crossmodal edges effectively connect the relevant nodes across modalities. Experiments on a large benchmark dataset (AudioSet) show that our model is state-of-the-art (0.53 mean average precision), outperforming transformer-based models and other graph-based models. Our code is available at github.com/AmirSh15/Cross modality grap