Recovering Faces from Portraits with Auxiliary Facial Attributes

Recovering a photorealistic face from an artistic portrait is a challenging task since crucial facial details are often distorted or completely lost in artistic compositions. To handle this loss, we propose an Attribute-guided Face Recovery from Portraits (AFRP) that utilizes a Face Recovery Network (FRN) and a Discriminative Network (DN). FRN consists of an autoencoder with residual block-embedded skip-connections and incorporates facial attribute vectors into the feature maps of input portraits at the bottleneck of the autoencoder. DN has multiple convolutional and fully-connected layers, and its role is to enforce FRN to generate authentic face images with corresponding facial attributes dictated by the input attribute vectors. %Leveraging on the spatial transformer networks, FRN automatically compensates for misalignments of portraits. % and generates aligned face images. For the preservation of identities, we impose the recovered and ground-truth faces to share similar visual features. Specifically, DN determines whether the recovered image looks like a real face and checks if the facial attributes extracted from the recovered image are consistent with given attributes. %Our method can recover high-quality photorealistic faces from unaligned portraits while preserving the identity of the face images as well as it can reconstruct a photorealistic face image with a desired set of attributes. Our method can recover photorealistic identity-preserving faces with desired attributes from unseen stylized portraits, artistic paintings, and hand-drawn sketches. On large-scale synthesized and sketch datasets, we demonstrate that our face recovery method achieves state-of-the-art results.Comment: 2019 IEEE Winter Conference on Applications of Computer Vision (WACV

Comparison of effect of resveratrol and vanadium on diabetes related dyslipidemia and hyperglycemia in streptozotocin induced diabetic rats

Purpose: Resveratrol a natural polyphenolic stilbene derivative has wide variety of biological activities. There is also a large body of evidence demonstrating positive effect of resveratrol in treatment of various metabolic complications including metabolic syndrome, obesity, diabetes and dyslipidemia in adults. The purpose of this study was to investigate anti-hyperglycemic and anti-dyslipidemic effects of resveratrol. Methods: We used 40 diabetic streptozotocin Wistar rats. Rats were randomly divided into 5 treatment groups (n=8 in each) including normal control, normal treated with resveratrol, diabetic control , diabetic treated with vanadium , diabetic treated with resveratrol . Resveratrol (25 mg/kgbw) and vanadate (0.2 mg/kgbw) was orally gavaged for 40 days and blood samples were directly collected from heart. Results: Diabetic rats treated with resveratrol in comparison to control diabetic rats demonstrated a significant (p = 0.001) decline in serum glucose concentration, and high plasma concentrations of total cholesterol and LDL-c were reduced (p = 0.031, p = 0.004 respectively). Furthermore, body weight loss trend that observed in diabetic rats alleviated by resveratrol and vanadate. However triglyceride, VLDL-c and HDL-c levels did not changed significantly. Conclusion: In conclusion Resveratrol ameliorated dyslipidemia and hyperglycemia in diabetic rats. However further investigations in peculiar human studies are required

Challenge of clinical education for critical care nursing students: qualitative content analysis

زمینه و هدف: آموزش بالینی بخش مهمی از آموزش دانشجویان پرستاری بخصوص دانشجویان کارشناسی ارشد پرستاری مراقبت ویژه است. لذا دقت نظر در خصوص آموزش بالینی از اهمیت ویژه ای برخوردار است. این مطالعه با هدف تبیین تجارب و چالشهای دانشجویان مقطع کارشناسی ارشد پرستاری مراقبت ویژه در خصوص آموزش بالینی طی رویکرد کیفی انجام شده است. روش بررسی: این مطالعه کیفی به روش تحلیل محتوای قراردادی در فاصله فروردین تا شهریور 1392 در دانشکده پرستاری و مامائی تهران انجام شده است. در مجموع 26 مصاحبه نیمه ساختارمند از 15نفر دانشجوی کارشناسی ارشد پرستاری مراقبت ویژه که با روش نمونه گیری هدفمند وارد مطالعه شدند، انجام شد. جمع آوری داده ها تا رسیدن به اشباع داده ها ادامه پیدا کرد. مدت مصاحبه ها بین 30 تا 60 دقیقه بود.تجزیه و تحلیل داده‌ها با روش آنالیز محتوای قراردادی انجام شد. یافته ها : از 15 شرکت کننده در مطالعه، 9 نفر زن و 6 نفر مرد بودند. دامنه سنی آنان بین 25 تا 34 سال بود. در مجموع 310کداولیه از متن مصاحبه‌ها استخراج شده که به دلیل تقریب مفهومی دو طبقه اصلی عوامل درونی و عوامل بیرونی شکل گرفت. در طبقه عوامل درونی زیر طبقات عدم هویت حرفه ای، عدم انگیزه و تجربه قبلی، و در طبقه عوامل بیرونی؛ تعاملات حرفه ای، عدم همخوانی آموزش نظزی و بالینی و مربی ناکارامد قرار گرفتند. بحث و نتیجه گیری: با توجه به یافته های پژوهش، عوامل درونی و بیرونی متعددی در آموزش بالینی دانشجویان کارشناسی ارشد پرستاری مراقبت ویژه لازم است وتوجه به این عوامل درونی وبیرونی منجر به افزایش یادگیری دانشجویان این رشته می شود. توجه به عوامل درونی همچون انگیزه دانشجویان، تجربه قبلی و هویت حرفه ای آنها و همچنین عوامل بیرونی همچون انتخاب مربیان کارامد وشایسته، تعاملات حرفه ای و فراهم اوردن محیط مناسب می تواند در رفع چالشهای آموزشی این دانشجویان کمک کننده باشد

Identity-preserving Face Recovery from Portraits

Recovering the latent photorealistic faces from their artistic portraits aids human perception and facial analysis. However, a recovery process that can preserve identity is challenging because the fine details of real faces can be distorted or lost in stylized images. In this paper, we present a new Identity-preserving Face Recovery from Portraits (IFRP) to recover latent photorealistic faces from unaligned stylized portraits. Our IFRP method consists of two components: Style Removal Network (SRN) and Discriminative Network (DN). The SRN is designed to transfer feature maps of stylized images to the feature maps of the corresponding photorealistic faces. By embedding spatial transformer networks into the SRN, our method can compensate for misalignments of stylized faces automatically and output aligned realistic face images. The role of the DN is to enforce recovered faces to be similar to authentic faces. To ensure the identity preservation, we promote the recovered and ground-truth faces to share similar visual features via a distance measure which compares features of recovered and ground-truth faces extracted from a pre-trained VGG network. We evaluate our method on a large-scale synthesized dataset of real and stylized face pairs and attain state of the art results. In addition, our method can recover photorealistic faces from previously unseen stylized portraits, original paintings and human-drawn sketches

Simultaneous Machine Translation with Large Language Models

Large language models (LLM) have demonstrated their abilities to solve various natural language processing tasks through dialogue-based interactions. For instance, research indicates that LLMs can achieve competitive performance in offline machine translation tasks for high-resource languages. However, applying LLMs to simultaneous machine translation (SimulMT) poses many challenges, including issues related to the training-inference mismatch arising from different decoding patterns. In this paper, we explore the feasibility of utilizing LLMs for SimulMT. Building upon conventional approaches, we introduce a simple yet effective mixture policy that enables LLMs to engage in SimulMT without requiring additional training. Furthermore, after Supervised Fine-Tuning (SFT) on a mixture of full and prefix sentences, the model exhibits significant performance improvements. Our experiments, conducted with Llama2-7B-chat on nine language pairs from the MUST-C dataset, demonstrate that LLM can achieve translation quality and latency comparable to dedicated SimulMT models

Cancer Stigma and its Consequences and Influencing Factors in Iranian Society: A Qualitative Study

Introduction: Stigma refers to a set of negative attitudes, beliefs, behaviors, and thoughts in dealing with a person who has a chronic disease or some health problems. Cancer is one of the diseases associated with stigma. Stigma causes harmful psycho-social effects for the affected person and family members and is considered an obstacle in disease screening and control programs. Accordingly, this study aimed to explore the nature of cancer stigma and its consequences and influencing factors in Iranian society.Methods: A total of 14 people including cancer patients, their families, and healthcare staff participated in this qualitative study. The participants were selected using purposive sampling and the data were collected through semi-structured interviews. The resulting data were analyzed using conventional content analysis and with MAXQDA software (version 10).Results: The content analysis revealed four themes including cancer as a terrifying and pitiful disease, identity crisis/psychosocial disintegration, disease complexity, and public unawareness and community problems.Conclusion: There are many negative beliefs and stereotypes about cancer and affected people, which are exacerbated by public unawareness and lack of sufficient information about cancer, as well as lack of comprehensive support. These beliefs and stereotypes adversely affect the quality of life of affected people. Following the findings of the study, some interventions need to be implemented to reduce stigma, increase the quality of life, and improve the treatment process for cancer patients

Investigation of Vorticity during Prevalent Winter Precipitation in Iran

Publisher's version (útgefin grein)In this study, precipitation data for 483 synoptic stations, and the U&V component of wind and HGT data for 4 atmospheric levels were respectively obtained from IRIMO and NCEP/NCAR databases (1961–2013). The precipitation threshold of 1 mm and a minimum prevalence of 50% were the criteria based on which the prevalent precipitation of Iran was identified. Then, vorticity of days corresponding to prevalent winter precipitation was calculated and, by performing cluster analysis, the representative days of vorticity were specified. The results showed that prevalent winter precipitation vorticity in Iran is related to the vorticity patterns of low pressure of Mediterranean-low pressure of Persian Gulf dual-core, low pressure closed of central Iran-high pressure of East Europe, Ural low pressure-Middle East High pressure, Saudi Arabia low pressure-Europe high pressure, and high-pressure belt of Siberia-low pressure of central Iran. At the same time, the most intense vorticity occurred when the climate of Iran was influenced by a massive belt pattern of Siberian high pressure-low pressure of central Iran. However, at the time of prevalent winter precipitation in Iran, an intense vorticity is drawn with the direction of Northeast and Northwest from the center of Iraq to the south of Iran.This work was supported by Vedurfelagid, Rannis, and Rannsoknastofa I VedurfraediPeer Reviewe

Estimates, trends, and drivers of the global burden of type 2 diabetes attributable to PM2.5 air pollution, 1990-2019 : an analysis of data from the Global Burden of Disease Study 2019

Background Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalence of diabetes, we aimed to quantify the burden of type 2 diabetes attributable to PM2.5 originating from ambient and household air pollution.Methods We systematically compiled all relevant cohort and case-control studies assessing the effect of exposure to household and ambient fine particulate matter (PM2.5) air pollution on type 2 diabetes incidence and mortality. We derived an exposure-response curve from the extracted relative risk estimates using the MR-BRT (meta-regression-Bayesian, regularised, trimmed) tool. The estimated curve was linked to ambient and household PM2.5 exposures from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, and estimates of the attributable burden (population attributable fractions and rates per 100 000 population of deaths and disability-adjusted life-years) for 204 countries from 1990 to 2019 were calculated. We also assessed the role of changes in exposure, population size, age, and type 2 diabetes incidence in the observed trend in PM2.5-attributable type 2 diabetes burden. All estimates are presented with 95% uncertainty intervals.Findings In 2019, approximately a fifth of the global burden of type 2 diabetes was attributable to PM2.5 exposure, with an estimated 3.78 (95% uncertainty interval 2.68-4.83) deaths per 100 000 population and 167 (117-223) disability-adjusted life-years (DALYs) per 100 000 population. Approximately 13.4% (9.49-17.5) of deaths and 13.6% (9.73-17.9) of DALYs due to type 2 diabetes were contributed by ambient PM2.5, and 6.50% (4.22-9.53) of deaths and 5.92% (3.81-8.64) of DALYs by household air pollution. High burdens, in terms of numbers as well as rates, were estimated in Asia, sub-Saharan Africa, and South America. Since 1990, the attributable burden has increased by 50%, driven largely by population growth and ageing. Globally, the impact of reductions in household air pollution was largely offset by increased ambient PM2.5.Interpretation Air pollution is a major risk factor for diabetes. We estimated that about a fifth of the global burden of type 2 diabetes is attributable PM2.5 pollution. Air pollution mitigation therefore might have an essential role in reducing the global disease burden resulting from type 2 diabetes. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd.Peer reviewe

Mapping 123 million neonatal, infant and child deaths between 2000 and 2017

Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2—to end preventable child deaths by 2030—we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000–2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low- and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained rates of 25 or fewer child deaths per 1,000 live births by 2017, and that 58% of child deaths between 2000 and 2017 in these countries could have been averted in the absence of geographical inequality. This study enables the identification of high-mortality clusters, patterns of progress and geographical inequalities to inform appropriate investments and implementations that will help to improve the health of all populations