Synthesis and Characterization of Silver Choromate Nanostructures via a Simple Precipitation Method

In summary, Ag2CrO4 nanostructures were prepared via a simple precipitation method by using [Ag(HSal)] as a new silver precursor. According to SEM images, the morphology of silver chromate nanostructures was 1-D and 3-D by using [Ag(HSal)] and AgNO3, respectively. Besides, SDS molecules were applied to decrease the particle size of the assynthesized products. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/3477

Maternal Characteristics and Clinical Diagnoses Influence Obstetrical Outcomes in Indonesia

This Indonesian study evaluates associations between near-miss status/death with maternal demographic, health care characteristics, and obstetrical complications, comparing results using retrospective and prospective data. The main outcome measures were obstetric conditions and socio-economic factors to predict near-miss/death. We abstracted all obstetric admissions (1,358 retrospective and 1,240 prospective) from two district hospitals in East Java, Indonesia between 4/1/2009 and 5/15/2010. Prospective data added socio-economic status, access to care and referral patterns. Reduced logistic models were constructed, and multivariate analyses used to assess association of risk variables to outcome. Using multivariate analysis, variables associated with risk of near-miss/death include postpartum hemorrhage (retrospective AOR 5.41, 95 % CI 2.64–11.08; prospective AOR 10.45, 95 % CI 5.59–19.52) and severe preeclampsia/ eclampsia (retrospective AOR 1.94, 95 % CI 1.05–3.57; prospective AOR 3.26, 95 % CI 1.79–5.94). Associations with near-miss/death were seen for antepartum hemorrhage in retrospective data (AOR 9.34, 95 % CI 4.34–20.13), and prospectively for poverty (AOR 2.17, 95 % CI 1.33–3.54) and delivering outside the hospital (AOR 2.04, 95 % CI 1.08–3.82). Postpartum hemorrhage and severe preeclampsia/ eclampsia are leading causes of near-miss/death in Indonesia. Poverty and delivery outside the hospital are significant risk factors. Prompt recognition of complications, timely referrals, standardized care protocols, prompt hospital triage, and structured provider education may reduce obstetric mortality and morbidity. Retrospective data were reliable, but prospective data provided valuable information about barriers to care and referral patterns

O-C Study of 545 Lunar Occultations from 13 Double Stars

International audienceIn this article, we have studied the reports of lunar occultations by this project observation's teams (named APTO) in comparison with other observations of the objects. Thirteen binary stars were selected for this study. All the previous observations of these stars were also collected. Finally, an analysis of O-C of all reports were performed

Intelligent evacuation management systems: A review

Crowd and evacuation management have been active areas of research and study in the recent past. Various developments continue to take place in the process of efficient evacuation of crowds in mass gatherings. This article is intended to provide a review of intelligent evacuation management systems covering the aspects of crowd monitoring, crowd disaster prediction, evacuation modelling, and evacuation path guidelines. Soft computing approaches play a vital role in the design and deployment of intelligent evacuation applications pertaining to crowd control management. While the review deals with video and nonvideo based aspects of crowd monitoring and crowd disaster prediction, evacuation techniques are reviewed via the theme of soft computing, along with a brief review on the evacuation navigation path. We believe that this review will assist researchers in developing reliable automated evacuation systems that will help in ensuring the safety of the evacuees especially during emergency evacuation scenarios

Artificial intelligence for photovoltaic systems

Photovoltaic systems have gained an extraordinary popularity in the energy generation industry. Despite the benefits, photovoltaic systems still suffer from four main drawbacks, which include low conversion efficiency, intermittent power supply, high fabrication costs and the nonlinearity of the PV system output power. To overcome these issues, various optimization and control techniques have been proposed. However, many authors relied on classical techniques, which were based on intuitive, numerical or analytical methods. More efficient optimization strategies would enhance the performance of the PV systems and decrease the cost of the energy generated. In this chapter, we provide an overview of how Artificial Intelligence (AI) techniques can provide value to photovoltaic systems. Particular attention is devoted to three main areas: (1) Forecasting and modelling of meteorological data, (2) Basic modelling of solar cells and (3) Sizing of photovoltaic systems. This chapter will aim to provide a comparison between conventional techniques and the added benefits of using machine learning methods

Implementation and evaluation of a harm-reduction model for clinical care of substance using pregnant women

<p>Abstract</p> <p>Background</p> <p>Methamphetamine (MA) use during pregnancy is associated with many pregnancy complications, including preterm birth, small for gestational age, preeclampsia, and abruption. Hawaii has lead the nation in MA use for many years, yet prior to 2007, did not have a comprehensive plan to care for pregnant substance-using women. In 2006, the Hawaii State Legislature funded a pilot perinatal addiction clinic. The Perinatal Addiction Treatment Clinic of Hawaii was built on a harm-reduction model, encompassing perinatal care, transportation, child-care, social services, family planning, motivational incentives, and addiction medicine. We present the implementation model and results from our first one hundred three infants (103) seen over 3 years of operation of the program.</p> <p>Methods</p> <p>Referrals came from community health centers, hospitals, addiction treatment facilities, private physician offices, homeless outreach services and self-referral through word-of-mouth and bus ads. Data to describe sample characteristics and outcome was obtained prospectively and retrospectively from chart abstraction and delivery data. Drug use data was obtained from the women's self-report and random urine toxicology during the pregnancy, as well as urine toxicology at the time of birth on mothers, and urine and meconium toxicology on the infants. Post-partum depression was measured in mothers with the Edinburgh Post-Partum depression scale. Data from Path clinic patients were compared with a representative cohort of women delivering at Kapiolani Medical Center for Women and Children during the same time frame, who were enrolled in another study of pregnancy outcomes. Ethical approval for this study was obtained through the University of Hawaii Committee for Human Studies.</p> <p>Results</p> <p>Between April 2007 and August 2010, 213 women with a past or present history of addiction were seen, 132 were pregnant and 97 delivered during that time. 103 live-born infants were delivered. There were 3 first-trimester Spontaneous Abortions, two 28-week intrauterine fetal deaths, and two sets of twins and 4 repeat pregnancies. Over 50% of the women had lost custody of previous children due to substance use. The majority of women who delivered used methamphetamine (86%), either in the year before pregnancy or during pregnancy. Other drugs include marijuana (59.8%), cocaine (33%), opiates (9.6%), and alcohol (15.2%). Of the women served, 85% smoked cigarettes upon enrollment. Of the 97 women delivered during this period, all but 4 (96%) had negative urine toxicology at the time of delivery. Of the 103 infants, 13 (12.6%) were born preterm, equal to the state and national average, despite having many risk factors for prematurity, including poverty, poor diet, smoking and polysubstance use. Overwhelmingly, the women are parenting their children, > 90% retained custody at 8 weeks. Long-term follow-up showed that women who maintained custody chose long-acting contraceptive methods; while those who lost custody had a very high (> 50%) repeat pregnancy rate at 9 months post delivery.</p> <p>Conclusion</p> <p>Methamphetamine use during pregnancy doesn't exist is isolation. It is often combined with a multitude of other adverse circumstances, including poverty, interpersonal violence, psychiatric comorbidity, polysubstance use, nutritional deficiencies, inadequate health care and stressful life experiences. A comprehensive harm reduction model of perinatal care, which aims to ameliorate some of these difficulties for substance-using women without mandating abstinence, provides exceptional birth outcomes and can be implemented with limited resources.</p

Shape recognition through multi-level fusion of features and classifiers

Shape recognition is a fundamental problem and a special type of image classification, where each shape is considered as a class. Current approaches to shape recognition mainly focus on designing low-level shape descriptors, and classify them using some machine learning approaches. In order to achieve effective learning of shape features, it is essential to ensure that a comprehensive set of high quality features can be extracted from the original shape data. Thus we have been motivated to develop methods of fusion of features and classifiers for advancing the classification performance. In this paper, we propose a multi-level framework for fusion of features and classifiers in the setting of gran-ular computing. The proposed framework involves creation of diversity among classifiers, through adopting feature selection and fusion to create diverse feature sets and to train diverse classifiers using different learn-Xinming Wang algorithms. The experimental results show that the proposed multi-level framework can effectively create diversity among classifiers leading to considerable advances in the classification performance

A multinational Delphi consensus to end the COVID-19 public health threat

Publisher Copyright: © 2022, The Author(s).Despite notable scientific and medical advances, broader political, socioeconomic and behavioural factors continue to undercut the response to the COVID-19 pandemic1,2. Here we convened, as part of this Delphi study, a diverse, multidisciplinary panel of 386 academic, health, non-governmental organization, government and other experts in COVID-19 response from 112 countries and territories to recommend specific actions to end this persistent global threat to public health. The panel developed a set of 41 consensus statements and 57 recommendations to governments, health systems, industry and other key stakeholders across six domains: communication; health systems; vaccination; prevention; treatment and care; and inequities. In the wake of nearly three years of fragmented global and national responses, it is instructive to note that three of the highest-ranked recommendations call for the adoption of whole-of-society and whole-of-government approaches1, while maintaining proven prevention measures using a vaccines-plus approach2 that employs a range of public health and financial support measures to complement vaccination. Other recommendations with at least 99% combined agreement advise governments and other stakeholders to improve communication, rebuild public trust and engage communities3 in the management of pandemic responses. The findings of the study, which have been further endorsed by 184 organizations globally, include points of unanimous agreement, as well as six recommendations with >5% disagreement, that provide health and social policy actions to address inadequacies in the pandemic response and help to bring this public health threat to an end.Peer reviewe