University of Jordan
About: University of Jordan is a(n) education organization based out in Amman, Jordan. It is known for research contribution in the topic(s): Population & Health care. The organization has 7796 authors who have published 13764 publication(s) receiving 213526 citation(s).
Papers published on a yearly basis
Daniel J. Klionsky1, Fábio Camargo Abdalla2, Hagai Abeliovich3, Robert T. Abraham4 +1284 more•Institutions (463)
TL;DR: These guidelines are presented for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes.
Abstract: In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field.
TL;DR: The qualitative and quantitative results prove the efficiency of SSA and MSSA and demonstrate the merits of the algorithms proposed in solving real-world problems with difficult and unknown search spaces.
Abstract: A novel optimization algorithm called Salp Swarm Optimizer (SSA) is proposed.Multi-objective Salp Swarm Algorithm (MSSA) is proposed to solve multi-objective problems.Both algorithms are tested on several mathematical optimization functions.Two challenging engineering design problems are solved: airfoil design and marine propeller design.The qualitative and quantitative results prove the efficiency of SSA and MSSA. This work proposes two novel optimization algorithms called Salp Swarm Algorithm (SSA) and Multi-objective Salp Swarm Algorithm (MSSA) for solving optimization problems with single and multiple objectives. The main inspiration of SSA and MSSA is the swarming behaviour of salps when navigating and foraging in oceans. These two algorithms are tested on several mathematical optimization functions to observe and confirm their effective behaviours in finding the optimal solutions for optimization problems. The results on the mathematical functions show that the SSA algorithm is able to improve the initial random solutions effectively and converge towards the optimum. The results of MSSA show that this algorithm can approximate Pareto optimal solutions with high convergence and coverage. The paper also considers solving several challenging and computationally expensive engineering design problems (e.g. airfoil design and marine propeller design) using SSA and MSSA. The results of the real case studies demonstrate the merits of the algorithms proposed in solving real-world problems with difficult and unknown search spaces.
TL;DR: A new definition of fractional derivative and fractional integral is given and it is shown that it is the most natural definition, and the most fruitful one.
Abstract: We give a new definition of fractional derivative and fractional integral. The form of the definition shows that it is the most natural definition, and the most fruitful one. The definition for [email protected][email protected]<1 coincides with the classical definitions on polynomials (up to a constant). Further, if @a=1, the definition coincides with the classical definition of first derivative. We give some applications to fractional differential equations.
TL;DR: The statistical results and comparisons show that the HHO algorithm provides very promising and occasionally competitive results compared to well-established metaheuristic techniques.
Abstract: In this paper, a novel population-based, nature-inspired optimization paradigm is proposed, which is called Harris Hawks Optimizer (HHO). The main inspiration of HHO is the cooperative behavior and chasing style of Harris’ hawks in nature called surprise pounce. In this intelligent strategy, several hawks cooperatively pounce a prey from different directions in an attempt to surprise it. Harris hawks can reveal a variety of chasing patterns based on the dynamic nature of scenarios and escaping patterns of the prey. This work mathematically mimics such dynamic patterns and behaviors to develop an optimization algorithm. The effectiveness of the proposed HHO optimizer is checked, through a comparison with other nature-inspired techniques, on 29 benchmark problems and several real-world engineering problems. The statistical results and comparisons show that the HHO algorithm provides very promising and occasionally competitive results compared to well-established metaheuristic techniques. Source codes of HHO are publicly available at http://www.alimirjalili.com/HHO.html and http://www.evo-ml.com/2019/03/02/hho .
University of Edinburgh1, University of Glasgow2, Johns Hopkins University3, University of Colorado Boulder4, University of the Witwatersrand5, International Military Sports Council6, Aga Khan University7, Medical Research Council8, King George's Medical University9, Kenya Medical Research Institute10, International Centre for Diarrhoeal Disease Research, Bangladesh11, Centers for Disease Control and Prevention12, University of Bergen13, Tribhuvan University14, University of Barcelona15, Utrecht University16, Emory University17, All India Institute of Medical Sciences18, University of Liverpool19, Boston Children's Hospital20, National Institute of Virology21, University of Zambia22, University of Health Sciences Antigua23, National Health Laboratory Service24, Chinese Center for Disease Control and Prevention25, Austral University26, University of Michigan27, Vanderbilt University28, University of New South Wales29, University of Auckland30, University of Otago31, Universidad del Valle de Guatemala32, University of Jordan33, University of Maryland, Baltimore34, National Scientific and Technical Research Council35, Research Institute for Tropical Medicine36, Pwani University College37, University of Cape Town38, University of Warwick39, Academy of Medical Sciences, United Kingdom40, Tohoku University41, École normale supérieure de Lyon42, John E. Fogarty International Center43, Charité44, Universidad Nacional de Asunción45, Tehran University of Medical Sciences46, Robert Koch Institute47, University of London48, University of New Mexico49, Capital Medical University50, Alaska Native Tribal Health Consortium51, Innlandet Hospital Trust52, Columbia University53, Mahidol University54, University of Pretoria55, Thailand Ministry of Public Health56, Peking Union Medical College57, Nagasaki University58, Public Health Foundation of India59
02 Sep 2017-The Lancet
TL;DR: In this paper, the authors estimated the incidence and hospital admission rate of RSV-associated acute lower respiratory infection (RSV-ALRI) in children younger than 5 years stratified by age and World Bank income regions.
Abstract: Summary Background We have previously estimated that respiratory syncytial virus (RSV) was associated with 22% of all episodes of (severe) acute lower respiratory infection (ALRI) resulting in 55 000 to 199 000 deaths in children younger than 5 years in 2005. In the past 5 years, major research activity on RSV has yielded substantial new data from developing countries. With a considerably expanded dataset from a large international collaboration, we aimed to estimate the global incidence, hospital admission rate, and mortality from RSV-ALRI episodes in young children in 2015. Methods We estimated the incidence and hospital admission rate of RSV-associated ALRI (RSV-ALRI) in children younger than 5 years stratified by age and World Bank income regions from a systematic review of studies published between Jan 1, 1995, and Dec 31, 2016, and unpublished data from 76 high quality population-based studies. We estimated the RSV-ALRI incidence for 132 developing countries using a risk factor-based model and 2015 population estimates. We estimated the in-hospital RSV-ALRI mortality by combining in-hospital case fatality ratios with hospital admission estimates from hospital-based (published and unpublished) studies. We also estimated overall RSV-ALRI mortality by identifying studies reporting monthly data for ALRI mortality in the community and RSV activity. Findings We estimated that globally in 2015, 33·1 million (uncertainty range [UR] 21·6–50·3) episodes of RSV-ALRI, resulted in about 3·2 million (2·7–3·8) hospital admissions, and 59 600 (48 000–74 500) in-hospital deaths in children younger than 5 years. In children younger than 6 months, 1·4 million (UR 1·2–1·7) hospital admissions, and 27 300 (UR 20 700–36 200) in-hospital deaths were due to RSV-ALRI. We also estimated that the overall RSV-ALRI mortality could be as high as 118 200 (UR 94 600–149 400). Incidence and mortality varied substantially from year to year in any given population. Interpretation Globally, RSV is a common cause of childhood ALRI and a major cause of hospital admissions in young children, resulting in a substantial burden on health-care services. About 45% of hospital admissions and in-hospital deaths due to RSV-ALRI occur in children younger than 6 months. An effective maternal RSV vaccine or monoclonal antibody could have a substantial effect on disease burden in this age group. Funding The Bill & Melinda Gates Foundation.
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|Debra K. Moser||85||558||27188|
|Ali H. Nayfeh||71||618||31111|
|Harold S. Margolis||71||199||26719|
|James E. Maynard||56||141||9158|
|E. Richard Moxon||54||176||10395|
|Liam G Heaney||53||234||8556|
|Stephen C. Hadler||52||148||11458|
|Nicholas H. Oberlies||52||262||9683|
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