Aswan University

Outcomes of chronic total occlusion (CTO) percutaneous coronary intervention (PCI) have improved because of advancements in equipment and techniques. With global collaboration and knowledge sharing, we have identified 7 common principles that are widely accepted as best practices for CTO-PCI. 1. Ischemic symptom improvement is the primary indication for CTO-PCI. 2. Dual coronary angiography and in-depth and structured review of the angiogram (and, if available, coronary computed tomography angiography) are key for planning and safely performing CTO-PCI. 3. Use of a microcatheter is essential for optimal guidewire manipulation and exchanges. 4. Antegrade wiring, antegrade dissection and reentry, and the retrograde approach are all complementary and necessary crossing strategies. Antegrade wiring is the most common initial technique, whereas retrograde and antegrade dissection and reentry are often required for more complex CTOs. 5. If the initially selected crossing strategy fails, efficient change to an alternative crossing technique increases the likelihood of eventual PCI success, shortens procedure time, and lowers radiation and contrast use. 6. Specific CTO-PCI expertise and volume and the availability of specialized equipment will increase the likelihood of crossing success and facilitate prevention and management of complications, such as perforation. 7. Meticulous attention to lesion preparation and stenting technique, often requiring intracoronary imaging, is required to ensure optimum stent expansion and minimize the risk of short- and long-term adverse events. These principles have been widely adopted by experienced CTO-PCI operators and centers currently achieving high success and acceptable complication rates. Outcomes are less optimal at less experienced centers, highlighting the need for broader adoption of the aforementioned 7 guiding principles along with the development of additional simple and safe CTO crossing and revascularization strategies through ongoing research, education, and training.

Abstract. In this paper, we describe the PALM model system 6.0. PALM (formerly an abbreviation for Parallelized Large-eddy Simulation Model and now an independent name) is a Fortran-based code and has been applied for studying a variety of atmospheric and oceanic boundary layers for about 20 years. The model is optimized for use on massively parallel computer architectures. This is a follow-up paper to the PALM 4.0 model description in Maronga et al. (2015). During the last years, PALM has been significantly improved and now offers a variety of new components. In particular, much effort was made to enhance the model with components needed for applications in urban environments, like fully interactive land surface and radiation schemes, chemistry, and an indoor model. This paper serves as an overview paper of the PALM 6.0 model system and we describe its current model core. The individual components for urban applications, case studies, validation runs, and issues with suitable input data are presented and discussed in a series of companion papers in this special issue.

BACKGROUND: Most data on mortality and prognostic factors in patients with heart failure come from North America and Europe, with little information from other regions. Here, in the International Congestive Heart Failure (INTER-CHF) study, we aimed to measure mortality at 1 year in patients with heart failure in Africa, China, India, the Middle East, southeast Asia and South America; we also explored demographic, clinical, and socioeconomic variables associated with mortality. METHODS: We enrolled consecutive patients with heart failure (3695 [66%] clinic outpatients, 2105 [34%] hospital in patients) from 108 centres in six geographical regions. We recorded baseline demographic and clinical characteristics and followed up patients at 6 months and 1 year from enrolment to record symptoms, medications, and outcomes. Time to death was studied with Cox proportional hazards models adjusted for demographic and clinical variables, medications, socioeconomic variables, and region. We used the explained risk statistic to calculate the relative contribution of each level of adjustment to the risk of death. FINDINGS: We enrolled 5823 patients within 1 year (with 98% follow-up). Overall mortality was 16·5%: highest in Africa (34%) and India (23%), intermediate in southeast Asia (15%), and lowest in China (7%), South America (9%), and the Middle East (9%). Regional differences persisted after multivariable adjustment. Independent predictors of mortality included cardiac variables (New York Heart Association Functional Class III or IV, previous admission for heart failure, and valve disease) and non-cardiac variables (body-mass index, chronic kidney disease, and chronic obstructive pulmonary disease). 46% of mortality risk was explained by multivariable modelling with these variables; however, the remainder was unexplained. INTERPRETATION: Marked regional differences in mortality in patients with heart failure persisted after multivariable adjustment for cardiac and non-cardiac factors. Therefore, variations in mortality between regions could be the result of health-care infrastructure, quality and access, or environmental and genetic factors. Further studies in large, global cohorts are needed. FUNDING: The study was supported by Novartis.

An efficient analytical (EA) method is proposed for optimally installing multiple distributed generation (DG) technologies to minimize power loss in distribution systems. Different DG types are considered, and their power factors are optimally calculated. The proposed EA method is also applied to the problem of allocating an optimal mix of different DG types with various generation capabilities. Furthermore, the EA method is integrated with the optimal power flow (OPF) algorithm to develop a new method, EA-OPF which effectively addresses overall system constraints. The proposed methods are tested using 33-bus and 69-bus distribution test systems. The calculated results are validated using the simulation results of the exact optimal solution obtained by an exhaustive OPF algorithm for both distribution test systems. The results show that the performances of the proposed methods are superior to existing methods in terms of computational speed and accuracy.

Importance: Understanding global variation in firearm mortality rates could guide prevention policies and interventions. Objective: To estimate mortality due to firearm injury deaths from 1990 to 2016 in 195 countries and territories. Design, Setting, and Participants: This study used deidentified aggregated data including 13 812 location-years of vital registration data to generate estimates of levels and rates of death by age-sex-year-location. The proportion of suicides in which a firearm was the lethal means was combined with an estimate of per capita gun ownership in a revised proxy measure used to evaluate the relationship between availability or access to firearms and firearm injury deaths. Exposures: Firearm ownership and access. Main Outcomes and Measures: Cause-specific deaths by age, sex, location, and year. Results: Worldwide, it was estimated that 251 000 (95% uncertainty interval [UI], 195 000-276 000) people died from firearm injuries in 2016, with 6 countries (Brazil, United States, Mexico, Colombia, Venezuela, and Guatemala) accounting for 50.5% (95% UI, 42.2%-54.8%) of those deaths. In 1990, there were an estimated 209 000 (95% UI, 172 000 to 235 000) deaths from firearm injuries. Globally, the majority of firearm injury deaths in 2016 were homicides (64.0% [95% UI, 54.2%-68.0%]; absolute value, 161 000 deaths [95% UI, 107 000-182 000]); additionally, 27% were firearm suicide deaths (67 500 [95% UI, 55 400-84 100]) and 9% were unintentional firearm deaths (23 000 [95% UI, 18 200-24 800]). From 1990 to 2016, there was no significant decrease in the estimated global age-standardized firearm homicide rate (-0.2% [95% UI, -0.8% to 0.2%]). Firearm suicide rates decreased globally at an annualized rate of 1.6% (95% UI, 1.1-2.0), but in 124 of 195 countries and territories included in this study, these levels were either constant or significant increases were estimated. There was an annualized decrease of 0.9% (95% UI, 0.5%-1.3%) in the global rate of age-standardized firearm deaths from 1990 to 2016. Aggregate firearm injury deaths in 2016 were highest among persons aged 20 to 24 years (for men, an estimated 34 700 deaths [95% UI, 24 900-39 700] and for women, an estimated 3580 deaths [95% UI, 2810-4210]). Estimates of the number of firearms by country were associated with higher rates of firearm suicide (P < .001; R2 = 0.21) and homicide (P < .001; R2 = 0.35). Conclusions and Relevance: This study estimated between 195 000 and 276 000 firearm injury deaths globally in 2016, the majority of which were firearm homicides. Despite an overall decrease in rates of firearm injury death since 1990, there was variation among countries and across demographic subgroups.

An increase in human activities and population growth have significantly increased the world's energy demands. The major source of energy for the world today is from fossil fuels, which are polluting and degrading the environment due to the emission of greenhouse gases. Hydrogen is an identified efficient energy carrier and can be obtained through renewable and non-renewable sources. An overview of renewable sources of hydrogen production which focuses on water splitting (electrolysis, thermolysis, and photolysis) and biomass (biological and thermochemical) mechanisms is presented in this study. The limitations associated with these mechanisms are discussed. The study also looks at some critical factors that hinders the scaling up of the hydrogen economy globally. Key among these factors are issues relating to the absence of a value chain for clean hydrogen, storage and transportation of hydrogen, high cost of production, lack of international standards, and risks in investment. The study ends with some future research recommendations for researchers to help enhance the technical efficiencies of some production mechanisms, and policy direction to governments to reduce investment risks in the sector to scale the hydrogen economy up.

Currently, most real-world time series datasets are multivariate and are rich in dynamical information of the underlying system. Such datasets are attracting much attention; therefore, the need for accurate modelling of such high-dimensional datasets is increasing. Recently, the deep architecture of the recurrent neural network (RNN) and its variant long short-term memory (LSTM) have been proven to be more accurate than traditional statistical methods in modelling time series data. Despite the reported advantages of the deep LSTM model, its performance in modelling multivariate time series (MTS) data has not been satisfactory, particularly when attempting to process highly non-linear and long-interval MTS datasets. The reason is that the supervised learning approach initializes the neurons randomly in such recurrent networks, disabling the neurons that ultimately must properly learn the latent features of the correlated variables included in the MTS dataset. In this paper, we propose a pre-trained LSTM-based stacked autoencoder (LSTM-SAE) approach in an unsupervised learning fashion to replace the random weight initialization strategy adopted in deep LSTM recurrent networks. For evaluation purposes, two different case studies that include real-world datasets are investigated, where the performance of the proposed approach compares favourably with the deep LSTM approach. In addition, the proposed approach outperforms several reference models investigating the same case studies. Overall, the experimental results clearly show that the unsupervised pre-training approach improves the performance of deep LSTM and leads to better and faster convergence than other models.

Many emerging economies, including the BRICS economies, are having difficulty meeting the Sustainable Development Goals’ (SDGs) objectives. Consequently, this research discusses the creation of an SDG framework for the BRICS economies, which can be utilized as a model for other blocs. To achieve this purpose, this research probes into the effect of biomass energy usage on ecological footprint in the BRICS economies between 1992 and 2018, considering the roles of gross capital formation, natural resources, and globalization. The novel Methods of Moments-Quantile-Regression (MMQR) approach with fixed effects is used, the outcomes of which reveal that in all quantiles (10th to 90th), globalization and biomass energy use mitigate environmental degradation, whereas economic growth, natural resources, and gross capital formation contribute to environmental degradation. The present research applied a series of techniques such as panel FMOLS, and DOLS, FE-OLS, the outcomes of which disclosed that globalization and biomass energy utilization help mitigate environmental degradation, while economic growth, natural resources, and gross capital formation improve environmental degradation. On the basis of the study’s findings, we suggest a shift in energy policies away from fossil fuels toward renewable energy alternatives by taking measures regarding the innovation of biomass to improve conversion efficiency.

There is a continuous and fast increase in electric vehicles (EVs) adoption in many countries due to the reduction of EVs prices, governments’ incentives and subsidies on EVs, the need for energy independence, and environmental issues. It is expected that EVs will dominate the private cars market in the coming years. These EVs charge their batteries from the power grid and may cause severe effects if not managed properly. On the other hand, they can provide many benefits to the power grid and get revenues for EV owners if managed properly. The main contribution of the article is to provide a review of potential negative impacts of EVs charging on electric power systems mainly due to uncontrolled charging and how through controlled charging and discharging those impacts can be reduced and become even positive impacts. The impacts of uncontrolled EVs charging on the increase of peak demand, voltage deviation from the acceptable limits, phase unbalance due to the single-phase chargers, harmonics distortion, overloading of the power system equipment, and increase of power losses are presented. Furthermore, a review of the positive impacts of controlled EVs charging and discharging, and the electrical services that it can provide like frequency regulation, voltage regulation and reactive power compensation, congestion management, and improving power quality are presented. Moreover, a few promising research topics that need more investigation in future research are briefly discussed. Furthermore, the concepts and general background of EVs, EVs market, EV charging technology, the charging methods are presented.

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.

Recently, solar energy has been intensively employed in power systems, especially using the photovoltaic (PV) generation units. In this regard, this paper proposes a novel design of a fuzzy logic based algorithm for varying the step size of the incremental conductance (INC) maximum power point tracking (MPPT) method for PV. In the proposed method, a variable voltage step size is estimated according to the degree of ascent or descent of the power-voltage relation. For this purpose, a novel unique treatment is proposed based on introducing five effective regions around the point of maximum PV power. To vary the step size of the duty cycle, a fuzzy logic system is developed according to the locations of the fuzzy inputs regarding the five regions. The developed fuzzy inputs are inspired from the slope of the power-voltage relation, namely the current-voltage ratio and its derivatives whereas appropriate membership functions and fuzzy rules are designed. The benefit of the proposed method is that the MPPT efficiency is improved for varying the step size of the incremental conductance method, thanks to the effective coordination between the proposed fuzzy logic based algorithm and the INC method. The output DC power of the PV array and the tracking speed are presented as indices for illustrating the improvement achieved in MPPT. The proposed method is verified and tested through the simulation of a grid-connected PV system model. The simulation results reveal a valuable improvement in static and dynamic responses over that of the traditional INC method with the variation of the environmental conditions. Further, it enhances the output dc power and reduce the convergence time to reach the steady state condition with intermittent environmental conditions.

Dual-function radar andcommunication (DRC) system has been recently recognized as a promising approach to solve the spectrum scarcity problem. However, when the target exists within a crowded area where pathloss dominating, the performance of radar may be severely degraded. To tackle this issue, this article proposes for the first time the deployment of an intelligent reflecting surface (IRS) to help the DRC system to enhance the radar detection performance. The IRS can configure the environment around the radar by adaptively adjusting the phases of its reflecting units to strengthen the signal quality toward specific directions, mostly the target direction, and completely null-out transmissions in other directions, mostly the directions toward the communication system. Specifically, in this article, we investigate the joint optimization of the IRS passive phase-shift matrix (PSM) and precoding matrix of the radar-aided basestation for the DRC system. The optimization is carried-out through maximizing the signal-to-noise ratio (SNR) at the radar receiver under both sensing and communication constraints, which turns out to be a nonconvex problem. In order to circumvent this challenging problem, an alternation optimization approach is employed to decouple the optimization variables and split this intractable problem into two subproblems. However, it is still challenging to obtain the optimal PSM due to the high power of the objective function and the unit-modulus constraints. To solve this problem, a majorization&#x2013;minimization algorithm is conceived to transform the nonconvex problem to an easy to solve quadratic constraint quadratic programming problem. Simulation resultsdemonstrate that the IRS can help improving the performance of the DRC system in terms of the received SNR, and the proposed algorithm shows fast convergence.

OBJECTIVES: Autism spectrum disorder (ASD) is a developmental disorder characterized by pervasive deficits in social interaction, impairment in verbal and non-verbal communication, and stereotyped patterns of interests and activities. Vitamin-D deficiency was previously reported in autistic children. However, the data on the relationship between vitamin D deficiency and the severity of autism are limited. METHODS: We performed a case-controlled cross-sectional analysis conducted on 122 ASD children, to assess their vitamin D status compared to controls and the relationship between vitamin D deficiency and the severity of autism. We also conducted an open trial of vitamin D supplementation in ASD children. RESULTS: Fifty-seven percent of the patients in the present study had vitamin D deficiency, and 30% had vitamin D insufficiency. The mean 25-OHD levels in patients with severe autism were significantly lower than those in patients with mild/moderate autism. Serum 25-OHD levels had significant negative correlations with Childhood Autism Rating Scale (CARS) scores. Of the ASD group, 106 patients with low-serum 25-OHD levels (<30 ng/ml) participated in the open label trial. They received vitamin D3 (300 IU/kg/day not to exceed 5000 IU/day) for 3 months. Eighty-three subjects completed 3 months of daily vitamin D treatment. Collectively, 80.72% (67/83) of subjects who received vitamin D3 treatment had significantly improved outcome, which was mainly in the sections of the CARS and aberrant behavior checklist subscales that measure behavior, stereotypy, eye contact, and attention span. CONCLUSION: Vitamin D is inexpensive, readily available and safe. It may have beneficial effects in ASD subjects, especially when the final serum level is more than 40 ng/ml. TRIAL REGISTRATION NUMBER: UMIN-CTR Study Design: trial Number: R000016846.

Catharanthus roseus is still the only source for the powerful antitumour drugs vinblastine and vincristine. Some other pharmaceutical compounds from this plant, ajmalicine and serpentine are also of economical importance. Although C. roseus has been studied extensively and was subject of numerous publications, a full characterization of its alkaloid pathway is not yet achieved. Here we review some of the recent work done on this plant. Most of the work focussed on early steps of the pathway, particularly the discovery of the 2-C-methyl-d-erythritol 4-phosphate (MEP)-pathway leading to terpenoids. Both mevalonate and MEP pathways are utilized by plants with apparent cross-talk between them across different compartments. Many genes of the early steps in Catharanthus alkaloid pathway have been cloned and overexpressed to improve the biosynthesis. Research on the late steps in the pathway resulted in cloning of several genes. Enzymes and genes involved in indole alkaloid biosynthesis and various aspects of their localization and regulation are discussed. Much progress has been made at alkaloid regulatory level. Feeding precursors, growth regulators treatments and metabolic engineering are good tools to increase productivity of terpenoid indole alkaloids. But still our knowledge of the late steps in the Catharanthus alkaloid pathway and the genes involved is limited.

BACKGROUND: The eastern Mediterranean region is comprised of 22 countries: Afghanistan, Bahrain, Djibouti, Egypt, Iran, Iraq, Jordan, Kuwait, Lebanon, Libya, Morocco, Oman, Pakistan, Palestine, Qatar, Saudi Arabia, Somalia, Sudan, Syria, Tunisia, the United Arab Emirates, and Yemen. Since our Global Burden of Disease Study 2010 (GBD 2010), the region has faced unrest as a result of revolutions, wars, and the so-called Arab uprisings. The objective of this study was to present the burden of diseases, injuries, and risk factors in the eastern Mediterranean region as of 2013. METHODS: GBD 2013 includes an annual assessment covering 188 countries from 1990 to 2013. The study covers 306 diseases and injuries, 1233 sequelae, and 79 risk factors. Our GBD 2013 analyses included the addition of new data through updated systematic reviews and through the contribution of unpublished data sources from collaborators, an updated version of modelling software, and several improvements in our methods. In this systematic analysis, we use data from GBD 2013 to analyse the burden of disease and injuries in the eastern Mediterranean region specifically. FINDINGS: The leading cause of death in the region in 2013 was ischaemic heart disease (90·3 deaths per 100 000 people), which increased by 17·2% since 1990. However, diarrhoeal diseases were the leading cause of death in Somalia (186·7 deaths per 100 000 people) in 2013, which decreased by 26·9% since 1990. The leading cause of disability-adjusted life-years (DALYs) was ischaemic heart disease for males and lower respiratory infection for females. High blood pressure was the leading risk factor for DALYs in 2013, with an increase of 83·3% since 1990. Risk factors for DALYs varied by country. In low-income countries, childhood wasting was the leading cause of DALYs in Afghanistan, Somalia, and Yemen, whereas unsafe sex was the leading cause in Djibouti. Non-communicable risk factors were the leading cause of DALYs in high-income and middle-income countries in the region. DALY risk factors varied by age, with child and maternal malnutrition affecting the younger age groups (aged 28 days to 4 years), whereas high bodyweight and systolic blood pressure affected older people (aged 60-80 years). The proportion of DALYs attributed to high body-mass index increased from 3·7% to 7·5% between 1990 and 2013. Burden of mental health problems and drug use increased. Most increases in DALYs, especially from non-communicable diseases, were due to population growth. The crises in Egypt, Yemen, Libya, and Syria have resulted in a reduction in life expectancy; life expectancy in Syria would have been 5 years higher than that recorded for females and 6 years higher for males had the crisis not occurred. INTERPRETATION: Our study shows that the eastern Mediterranean region is going through a crucial health phase. The Arab uprisings and the wars that followed, coupled with ageing and population growth, will have a major impact on the region's health and resources. The region has historically seen improvements in life expectancy and other health indicators, even under stress. However, the current situation will cause deteriorating health conditions for many countries and for many years and will have an impact on the region and the rest of the world. Based on our findings, we call for increased investment in health in the region in addition to reducing the conflicts. FUNDING: Bill & Melinda Gates Foundation.

Covering: up to December 2017 The diversity of secondary metabolites in the fungal order Xylariales is reviewed with special emphasis on correlations between chemical diversity and biodiversity as inferred from recent taxonomic and phylogenetic studies. The Xylariales are arguably among the predominant fungal endophytes, which are the producer organisms of pharmaceutical lead compounds including the antimycotic sordarins and the antiparasitic nodulisporic acids, as well as the marketed drug, emodepside. Many Xylariales are "macromycetes", which form conspicuous fruiting bodies (stromata), and the metabolite profiles that are predominant in the stromata are often complementary to those encountered in corresponding mycelial cultures of a given species. Secondary metabolite profiles have recently been proven highly informative as additional parameters to support classical morphology and molecular phylogenetic approaches in order to reconstruct evolutionary relationships among these fungi. Even the recent taxonomic rearrangement of the Xylariales has been relying on such approaches, since certain groups of metabolites seem to have significance at the species, genus or family level, respectively, while others are only produced in certain taxa and their production is highly dependent on the culture conditions. The vast metabolic diversity that may be encountered in a single species or strain is illustrated based on examples like Daldinia eschscholtzii, Hypoxylon rickii, and Pestalotiopsis fici. In the future, it appears feasible to increase our knowledge of secondary metabolite diversity by embarking on certain genera that have so far been neglected, as well as by studying the volatile secondary metabolites more intensively. Methods of bioinformatics, phylogenomics and transcriptomics, which have been developed to study other fungi, are readily available for use in such scenarios.

This study investigates the convective heat transfer of a hybrid nanofluid filled in a triangular cavity subjected to a constant magnetic field and heated by a constant heat flux element from below. The inclined side of the cavity is cooled isothermally while the remaining sides are thermally insulated. The finite difference method with the stream function-vorticity formulation of the governing equations has been utilized in the numerical solution. The problem is governed by several pertinent parameters namely, the size and position of the heater element, B = 0.2–0.8 and D = 0.3–0.7, respectively, the Rayleigh number, Ra = 102–106, the Hartmann number, Ha = 0–100, the volume fraction of the suspended nanoparticles, ϕ = 0–0.2, and the heat generation parameter Q = 0–6. The results show significant effect of increasing the volume fraction of the hybrid nanofluid when the natural convection is very small. Moreover, the hybrid nanofluid composed of equal quantities of Cu and Al2O3 nanoparticles dispersed in water base fluid has no significant enhancement on the mean Nusselt number compared with the regular nanofluid.

The residential load sector plays a vital role in terms of its impact on overall power balance, stability, and efficient power management. However, the load dynamics of the energy demand of residential users are always nonlinear, uncontrollable, and inelastic concerning power grid regulation and management. The integration of distributed generations (DGs) and advancement of information and communication technology (ICT) even though handles the related issues and challenges up to some extent, till the flexibility, energy management and scheduling with better planning are necessary for the residential sector to achieve better grid stability and efficiency. To address these issues, it is indispensable to analyze the demand-side management (DSM) for the complex residential sector considering various operational constraints, objectives, identifying various factors that affect better planning, scheduling, and management, to project the key features of various approaches and possible future research directions. This review has been done based on the related literature to focus on modeling, optimization methods, major objectives, system operation constraints, dominating factors impacting overall system operation, and possible solutions enhancing residential DSM operation. Gaps in future research and possible prospects have been discussed briefly to give a proper insight into the current implementation of DSM. This extensive review of residential DSM will help all the researchers in this area to innovate better energy management strategies and reduce the effect of system uncertainties, variations, and constraints.

BACKGROUND: Past research in population health trends has shown that injuries form a substantial burden of population health loss. Regular updates to injury burden assessments are critical. We report Global Burden of Disease (GBD) 2017 Study estimates on morbidity and mortality for all injuries. METHODS: We reviewed results for injuries from the GBD 2017 study. GBD 2017 measured injury-specific mortality and years of life lost (YLLs) using the Cause of Death Ensemble model. To measure non-fatal injuries, GBD 2017 modelled injury-specific incidence and converted this to prevalence and years lived with disability (YLDs). YLLs and YLDs were summed to calculate disability-adjusted life years (DALYs). FINDINGS: In 1990, there were 4 260 493 (4 085 700 to 4 396 138) injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554) deaths in 2017, while age-standardised mortality decreased from 1079 (1073 to 1086) to 738 (730 to 745) per 100 000. In 1990, there were 354 064 302 (95% uncertainty interval: 338 174 876 to 371 610 802) new cases of injury globally, which increased to 520 710 288 (493 430 247 to 547 988 635) new cases in 2017. During this time, age-standardised incidence decreased non-significantly from 6824 (6534 to 7147) to 6763 (6412 to 7118) per 100 000. Between 1990 and 2017, age-standardised DALYs decreased from 4947 (4655 to 5233) per 100 000 to 3267 (3058 to 3505). INTERPRETATION: Injuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017. Future research in injury burden should focus on prevention in high-burden populations, improving data collection and ensuring access to medical care.

High step-up DC/DC converter and maximum power point tracking (MPPT) control are essential components in photovoltaic (PV) systems. For the purpose of utilizing PV module in power generation, this manuscript proposes 1-new high stepup DC/DC converter 2-model predictive control based maximum power point tracking (MPC-MPPT) algorithm with optimum number of sensors. The suggested topology is able to provide a voltage gain up to 10 times of input-voltage and its measured efficiency is around 93%. MPC is a prevalent control technique with superior transient and steady-state performances in PV systems. However, in PV DC/DC converters, conventional MPC based MPPT technique typically requires two voltage-sensors and one current-sensor. For the purpose of reducing system cost, this manuscript presents MPC based MPPT technique with twosensors. The algorithm is designed to operate with both fixed and adaptive step-size. Different scenarios and operating conditions are evaluated both in Simulink and with hardware set-up. Results obtained from the simulation and experimental work are consistent and verify the analytical analysis of the system. Index Terms-DC/DC converter, model predictive control based maximum power point tracking (MPC-MPPT). I. IntroductIon I N photovoltaic (PV) generation systems, a DC/DC converter is required to link the low voltage PV panel and the high voltage DC link. In this DC/DC converter, maximum-powerpoint-tracking (MPPT) control is required to fully exploit the capacity of the PV panel[1]-[2] . In general, high tracking accuracy, and stable transient and steady-state response are important criteria to evaluate the performance of MPPT techniques. In order to achieve such criteria, different MPPT techniques have been investigated in literature [3]-[6].