Statistical-Synoptic Analysis of April 2019 Heavy Rainfall in Doroud-Boroujerd Basin

The occurrence of catastrophic floods in March-April 2019 in Lorestan province was a clear example of heavy rains that caused very heavy damage to agricultural, urban, transportation, and communications infrastructure.  The purpose of this study is to investigate the March-April 2019 rainfall in the Droud-Borujerd catchment area in terms of statistical, synoptic, and dynamic characteristics. In this regard, from the data related to the daily station rainfall in March-April 2019 of Boroujerd and Doroud synoptic stations, NOAA climate Synoptic factor data for the 25th March and 2nd April 2019, and upper atmospheric data from the University of Wyoming database for the mentioned days of April 2019. The results of statistical analysis showed that the occurrence of rainfall in April 2019 was one of the heavy rains that in the first wave (25th March) 2019 was 15% of the total annual rainfall and in the second wave (2nd April 2019) 20% of the total annual rainfall was recorded. Analysis of synoptic patterns of these heavy rainfall events showed that a similar synoptic pattern produced these two waves of heavy rainfall in the region. On both days, the presence of a strong trough a height of 5500 and 5550 geopotential meters, on the east of the Mediterranean Sea that the western region of Iran located in the front of this trough, lead to heavy rainfall. In these two days, the omega index had reached a significant critical value (-0.2). Moisture injection in the study area was done by the interaction of two cyclonic systems (east of the Mediterranean Sea) and anti-cyclone (on the Gulf of Aden) and the source of moisture supply was the Mediterranean Sea, the Red Sea, and the Persian Gulf, respectively. High atmospheric instability indices did not confirm the existence of very severe instability in the region. Moderate instability in the lower levels of the atmosphere, which could not be extended to the upper level (Skew-T diagram), indicated that a global synoptic system was involved in the whole region and no local convection factor played a role

Ore Genesis of the Abu Ghalaga Ferro-Ilmenite Ore Associated with Neoproterozoic Massive-Type Gabbros, South-Eastern Desert of Egypt: Evidence from Texture and Mineral Chemistry

Massif-type mafic intrusions (gabbro and anorthosite) are known for their considerable resources of vanadium-bearing iron–titanium oxide ores. Massive-type gabbroic and anorthosite rocks are frequently associated with magmatic rocks that have significant quantities of iron, titanium, and vanadium. The most promising intrusions that host Fe-Ti oxide ores are the gabbroic rocks in the south-eastern desert. The ilmenite ore deposits are hosted in arc gabbroic and anorthosite rocks. They are classified into three types, namely black ore, red ore, and disseminated ore. The black ilmenite ore is located at the deeper level, while the oxidized red ore is mainly located at or near the surface. Petrographically, the gabbro and ilmenite ores indicate a crystallization sequence of plagioclase, titaniferous pyroxene, and ilmenite. This reveals that the ilmenite is a magmatic deposit formed by the liquid gravity concentration of ilmenite following the crystallization of feldspar and pyroxene. Meanwhile, quartz, tremolite, zoisite, and opaque minerals are accessory minerals. The Fe-Ti ores are composed of ilmenite hosting exsolved hematite lamellae of variable sizes and shapes, gangue silicate minerals, and some sulfides. The X-ray diffraction (XRD) data reveal the presence of two mineral phases: ilmenite and hematite formed by the unmixing of the ferroilmenite homogeneous phase upon cooling. As a result, the ore is mostly made up of hemo-ilmenite. Using an electron microscope (SEM), as well as by observing the textures seen by the ore microscope, ilmenite is the dominant Fe-Ti oxide and contains voluminous hematite exsolved crystals. Under the scanning electron microscope, ilmenite contained intergrowths of hematite as a thin sandwich and lens shape. The formation of hematite lamellae indicates an oxidation process. Mineral chemistry-based investigations reveal late/post-magmatic activity at high temperatures. The examined ilmenite plots on the ferro-ilmenite line were created by continuous solid solution over 800 °C, whereas the analyzed magnetite and Ti-magnetite plot near the magnetite line and were formed by continuous solid solution exceeding 600 °C

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. Methods The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model—a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates—with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality—which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. Findings The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2–100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1–290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1–211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4–48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3–37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7–9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. Interpretation Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere

Determinants of variation in household energy choice and consumption: Case from Mahabad City, Iran

This study seeks to find a method to identify the dominant pattern of energy choice and consumption in households, centering on demographic factors affecting the use of home appliances. To this aim, this study dealt with a variety of energy sources widely used by households, namely, liquefied petroleum gas (LPG), electricity, and kerosene for cooking, heating and cooling, lighting, and home appliances. Additionally, significant associations for the household energy choice and consumption were identified for demographic variables including household size, gender, head-of-household age, educational level, and income group. A logistic regression analysis was performed to obtain quantitative data provided by a survey from 821 households across residential districts of urban and rural areas in Mahabad city, northwest Iran. Obtained data were analyzed within a proposed three-energy dimension model (3-ED). The results showed that, in the case of other variables remaining constant, income may lead to variation in LPG and electricity consumption. Unlike other independent variables, the head-of-household age failed to have a significant impact. The findings can contribute to a better understanding of effective factors got household energy choice and consumption in other cities, and they can be useful for the support of policy-makers in their consumption patterns

Impact of household demographic characteristics on energy conservation and carbon dioxide emission: Case from Mahabad city, Iran

This study explores the impact of different household demographic characteristics on energy conservation and carbon dioxide (CO2) emission in Mahabad city located in the northwest of Iran. The structural model adopted was composed of six variables, including household age, household size, educational qualification, income quintile, gender, and energy conservation concerning demographic characteristics and energy sources and consumptions. To compare predictability power of effects of these variables concerning households’ energy conservation and CO2 emissions, a crisp instruction on how to evolve a statistical technique for analyzing data was provided by partial least squares structural equation modeling (PLS-SEM). To verify the reliability of the PLS-SEM technique, the statistical significance test was performed by investigating path coefficients. The study revealed that households consume approximately 89.71% on liquefied petroleum gas (LPG), 9.87% on electricity while the rest 0.43% on kerosene, petrol, and diesel monthly. Eventually, the results of this study showed that household age, household size, and carbon dioxide emissions, except education background and income level, are significantly correlated with energy conservation

Application of Multi-Criteria Decision-Making Model and Expert Choice Software for Coastal City Vulnerability Evaluation

Climate change is regarded as a serious threat to both environment and humanity, and as a result, it has piqued worldwide attention in the twenty-first century. Natural hazards are expected to have major effects in the coastal cities of the globe. At the same time, about two-thirds of the world’s human population lives in the coastal margins. One of the fundamental issues for coastal city planners is the coastal cities’ environmental change. This paper presents the application of a model framework for the management and sustainable development of coastal cities under a changing climate in Kuala Terengganu Malaysia. The analytic hierarchy process (AHP) is performed in the Expert Choice software for coastal city hazard management. This approach enables decision-makers to evaluate and identify the relative priorities of vulnerability and hazard criteria and sub-criteria based on a set of preferences, criteria, and alternatives. This paper also presents a hierarchy erosion design applied in Kuala Terengganu to choose the important sustainable weights of criteria and sub-criteria as well as the zone as an alternative model

Land-Use Suitability Assessment Using Delphi and Analytical Hierarchy Process (D-AHP) Hybrid Model for Coastal City Management: Kuala Terengganu, Peninsular Malaysia

Since at least half of the world’s population resides and works within coastal land, the coastal zone processes and resource management is of great economic and social importance. One of the fundamental issues for coastal city planners, researchers, managers, and engineers is the coastal city land-use suitability. Land-use suitability is the ability of a given type of land to support a defined use. Rapid urbanization and consequent haphazard growth of cities result in deterioration of infrastructure facilities, loss of agricultural land, water bodies, open spaces, and many micro-climatic changes. Hence, accurate data on coastal city hazards are essential and valuable tools for coastal planning and management, sustainable coastal development, coastal environment conservation, selection of a site for coastal city structures, and coastal resources. In this investigation, the Delphi and Analytical Hierarchy Process (D-AHP) Hybrid model and Geographic Information System (GIS) technique for Coastal Land-Use Assessment (CLUA) are mapped to detect the most suitable and unsuitable areas in the Kuala Terengganu coastal zone. Furthermore, this research offered information not only on the present urban land-use trend and established amenity status in Kuala Terengganu, but also on the suitability of land for the potential establishment of urban facilities for improved urban planning and appropriate decision-making. Using the D-AHP Hybrid model and GIS tool for coastal city management is broadly practical for government, policymakers, and planners to appropriately strategize and plan for the future of coastal cities in Malaysia and other analog coastal cities around the world