Robust Shortest Path Problem: Models and Solution Algorithms

Shortest path is a key component of several network related problems and has been widely used and applied in numerous disciplines such as transportation, logistics and telecommunication networks. This problem in the base deterministic settings lends itself to elegant and efficient solution methods. Nevertheless, the initial formulation is limited in number of ways; one such limitation is the need to accounting for inherent uncertainty in real world transportation networks. In recent years there has been a growing interest in incorporating uncertainty within the transportation network analysis models and particularly the shortest path problem. This dissertation contributes to the growing body of literature in dealing with uncertainty in shortest path problem by developing formulations as well as efficient solution methodologies for these class of problems.;There are number of approaches across the literature for incorporating the stochastic features of network related parameters such as travel time into the shortest path problem. One such approach is to minimize mean-risk analysis which is to minimize both the average cost and the risks arising from the uncertainty assumptions. The chief complication of such modeling approach is that the size of the nonlinear part of the objective function will increase for the large size real world network problem which undermines the efficiency of the existing solution approach. In response to such needs a solution methodology based on outer approximation (OA) strategy is proposed and customized which is highly efficient for real world large size instances.;In addition, in this dissertation a robust optimization approach for the shortest path problem where travel cost is uncertain and exact information on the distribution function is unavailable has been applied. Robust shortest path under such conditions is shown to be formulated as a binary nonlinear integer program, which can then be reformulated as a mixed integer conic quadratic program.;Finally, both two modeling frameworks provide a generalization in which links have two cost components, representing the expected cost and risk measure on the links -- the former term is additive, but the latter is not. In the third and final part of this dissertation, a solution methodology for general formulation of shortest path problem with non-additive continuous convex travel cost functions is presented

Investigating Cause and Effect Relationships and Prioritizing of GM Assessment Indexes based on Economic, Resources, Energy and Environmental Attributes and PSR Framework using Gray DEMATAL

Nowadays the role of green manufacturing (GM) in sustainable development is evident and irrefutable therefore organizations seek to introduce themselves green in order to maintain their image toward their community. The usual method of sustainability and greenness assessment of a system is making use of indicators and indexes which are classified into several groups based on their characteristics. An important type of index categorization is based on four sustainability attributes including economic, energy, environment and recourses as well as pressure-state-response model (PSR). Because of the research gap about interactions relationships on indexes and investigating their influence others and influence by others. Since, indexes in each group could be effective on other indexes and be overlapped to some extent, it is necessary to prioritize and evaluate cause and effect relations by use of an appropriate method. We consider the relationship and prioritize most important indexes to evaluate manufacturing' greenness based on aforementioned sustainability attributes and PSR model. Purpose data is gathered by survey GM experts questionnaires, including 41 indexes plus 4 mentioned attributes, totally as 45 factors in 13 groups. In order to data analysis, with respect to the non-certainty and insufficient information, Grey DEMATEL method is used.Atualmente, o papel da manufatura verde (GM, Green Manufacturing) no desenvolvimento sustentável é evidente e irrefutável, portanto, as organizações procuram se apresentar “verdes” para manter sua imagem em sua comunidade. O método usual de avaliação da sustentabilidade e do verdor de um sistema é o uso de indicadores e índices que são classificados em vários grupos com base em suas características. Um tipo importante de categorização de índices é baseado em quatro atributos de sustentabilidade, incluindo econômico, energia, meio ambiente e recursos, além do modelo pressão-resposta-estado (PSR, Pressure-State-Response). Tendo em vista a lacuna de pesquisa sobre as relações de interações em índices faz-se necessário investigar a influência de outros e quais são influenciados por outros. Como os índices em cada grupo podem ser efetivos em outros índices e serem sobrepostos em certa medida, assim é essencial priorizar e avaliar as relações de causa e efeito pelo uso de um método apropriado. Consideramos o relacionamento e priorizamos os índices mais importantes para avaliar o verdor da manufatura com base nos atributos de sustentabilidade e no modelo de PSR. Os dados são coletados por questionários especializados em GM, incluindo 41 índices mais os 4 atributos mencionados, totalizando 45 fatores em 13 grupos. A fim de analisar os dados, no que diz respeito às informações não seguras e insuficientes, é utilizado o método Gray DEMATEL

On the capability of in-situ exposure in an environmental scanning electron microscope for investigating the atmospheric corrosion of magnesium

The feasibility of environmental scanning electron microscope (BEM) in studying the atmospheric corrosion behavior of 99.97% Mg was investigated. For reference, ex-situ exposure was performed. A model system was designed by spraying few salt particles on the metal surface and further promoting the corrosion process using platinum (Pt) deposition in the form of 1 x 1 x 1 pm(3) dots around the salt particles to create strong artificial cathodic sites. The results showed that the electron beam play a significant role in the corrosion process of scanned regions. This was attributed to the irradiation damage occurring on the metal surface during the BEM in-situ experiment. After achieving to a reliable process route, in a successful attempt, the morphology and composition of the corrosion products formed in-situ in the ESEM were in agreement with those of the sample exposed ex-situ

On the early stages of localised atmospheric corrosion of magnesium–aluminium alloys

The surface film on pure magnesium and two aluminium-containing magnesium alloys was characterised after 96\ua0h at 95% RH and 22\ua0\ub0C. The concentration of CO2 was carefully controlled to be either 0 or 400\ua0ppm. The exposed samples were investigated using X-ray photoelectron spectroscopy, Fourier transform infrared spectroscopy, X-ray diffraction, and electron microscopy. The results showed that when the alloys were exposed to the CO2-containing environment, aluminium cations (Al3+) was incorporated into a layered surface film comprising a partially “hydrated” MgO layer followed by Mg(OH)2, and magnesium hydroxy carbonates. The results indicated that aluminium-containing magnesium alloys exhibited considerably less localised corrosion in humid air than pure magnesium. Localised corrosion in the materials under investigation was attributed to film thinning by a dissolution/precipitation mechanism

Prostorna analiza električne vodljivosti podzemnih voda pomoću običnoga kriginga i metoda umjetne inteligencije (slučaj ravnice Tabriz, Iran)

rtificial intelligence (AI) systems have opened a new horizon to analyze water engineering and environmental problems in recent decades. In this study performances of ordinary kriging (OK) as a linear geostatistical estimator and two intelligent methods including artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are investigated. For this purpose, geographical coordinates of 120 observation wells that located in Tabriz plain, north-west of Iran, were defined as inputs and groundwater electrical conductivities (EC) were set as output of models. Eighty percent of data were randomly selected to train and develop mentioned models and twenty percent of data used for testing and validating. Finally, the outputs of models were compared with the corresponding measured values in observation wells. Results indicated that ANFIS model provided the best accuracy among models with the root mean squared error (RMSE) value of 1.69 dS.m–1 and correlation coefficient (R) of 0.84. The RMSE values in ANN and OK were calculated 1.97 and 2.14 dS.m–1 and the R values were determined 0.79 and 0.76, respectively. According to the results, the ANFIS method predicted EC precisely and can be advised for modeling groundwater salinity.u posljednjih nekoliko desetljeća sustavi umjetne inteligencije (AI) su otvorili nove horizonte u analizi problema vodnog inženjeringa te ekoloških problema. U ovoj studiji istražene su performanse običnog kriginga (OK) kao geostatističkog procjenitelja te performanse dvaju naprednih metoda, prva od kojih je umjetna neuronska mreža (ANN), a druga je hibridni sustav ANFIS (Adaptive Neuro-Fuzzy Inference System) koji uz neuronsku mrežu uključuje i neizravnu (fuzzy) logiku. U tu svrhu, zemljopisne koordinate 120 mjernih bunara lociranih u ravnici Tabriz u sjeverozapadnom Iranu definirane su kao ulazi, a električne vodljivosti (EC) podzemnih voda postavljeni su kao izlazi modela. Osamdeset posto podataka nasumce je izabrano za razvoj i obuku (učenje) navedenih modela, a dvadeset posto podataka iskorišteno je za testiranje i provjeru. Na kraju, izlazi modela su uspoređeni s odgovarajućim mjerenim vrijednostima u mjernim bunarima. Rezultati su pokazali da model ANFIS među svim promatranim modelima daje najbolju točnost s korijenom srednje kvadratne pogreške (RMSE) od 1,69 dS.m–1 i koeficijentom korelacije (R) od 0,84. Izračunate vrijednosti RMSE u modelima ANN i OK iznose 1.97, odnosno 2.14 dS.m–1, a koeficijenata korelacije 0,79, odnosno 0,76, respektivno. Prema dobivenim rezultatima ANFIS metoda je precizno predvidjela električnu vodljivost te se stoga može preporučiti za modeliranje saliniteta podzemnih voda

Surface preparation of powder metallurgical tool steels by means of wire electrical discharge machining

The surface of two types of powder metallurgical (PM) tool steels (i.e., with and without nitrogen) was prepared using wire electrical discharge machining (WEDM). From each grade of tool steel, seven surfaces corresponding to one to seven passes of WEDM were prepared. The WEDM process was carried out using a brass wire as electrode and deionized water as dielectric. After eachWEDM pass the surface of the tool steels was thoroughly examined. Surface residual stresses were measured by the X-ray diffraction (XRD) technique. The measured stresses were found to be of tensile nature. The surface roughness of the WEDM specimens was measured using interference microscopy. The surface roughness as well as the residual stress measurements indicated an insignificant improvement of these parameters after four passes of WEDM. In addition, the formed recast layer was characterized by means of scanning electron microscopy (SEM), XRD, and X-ray photoelectron spectroscopy (XPS). The characterization investigation clearly shows diffusion of copper and zinc from the wire electrode into the work material, even after the final WEDM step. Finally, the importance of eliminating excessive WEDM steps is thoroughly discussed

Global burden of chronic respiratory diseases and risk factors, 1990–2019: an update from the Global Burden of Disease Study 2019

Background: Updated data on chronic respiratory diseases (CRDs) are vital in their prevention, control, and treatment in the path to achieving the third UN Sustainable Development Goals (SDGs), a one-third reduction in premature mortality from non-communicable diseases by 2030. We provided global, regional, and national estimates of the burden of CRDs and their attributable risks from 1990 to 2019. Methods: Using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we estimated mortality, years lived with disability, years of life lost, disability-adjusted life years (DALYs), prevalence, and incidence of CRDs, i.e. chronic obstructive pulmonary disease (COPD), asthma, pneumoconiosis, interstitial lung disease and pulmonary sarcoidosis, and other CRDs, from 1990 to 2019 by sex, age, region, and Socio-demographic Index (SDI) in 204 countries and territories. Deaths and DALYs from CRDs attributable to each risk factor were estimated according to relative risks, risk exposure, and the theoretical minimum risk exposure level input. Findings: In 2019, CRDs were the third leading cause of death responsible for 4.0 million deaths (95% uncertainty interval 3.6–4.3) with a prevalence of 454.6 million cases (417.4–499.1) globally. While the total deaths and prevalence of CRDs have increased by 28.5% and 39.8%, the age-standardised rates have dropped by 41.7% and 16.9% from 1990 to 2019, respectively. COPD, with 212.3 million (200.4–225.1) prevalent cases, was the primary cause of deaths from CRDs, accounting for 3.3 million (2.9–3.6) deaths. With 262.4 million (224.1–309.5) prevalent cases, asthma had the highest prevalence among CRDs. The age-standardised rates of all burden measures of COPD, asthma, and pneumoconiosis have reduced globally from 1990 to 2019. Nevertheless, the age-standardised rates of incidence and prevalence of interstitial lung disease and pulmonary sarcoidosis have increased throughout this period. Low- and low-middle SDI countries had the highest age-standardised death and DALYs rates while the high SDI quintile had the highest prevalence rate of CRDs. The highest deaths and DALYs from CRDs were attributed to smoking globally, followed by air pollution and occupational risks. Non-optimal temperature and high body-mass index were additional risk factors for COPD and asthma, respectively. Interpretation: Albeit the age-standardised prevalence, death, and DALYs rates of CRDs have decreased, they still cause a substantial burden and deaths worldwide. The high death and DALYs rates in low and low-middle SDI countries highlights the urgent need for improved preventive, diagnostic, and therapeutic measures. Global strategies for tobacco control, enhancing air quality, reducing occupational hazards, and fostering clean cooking fuels are crucial steps in reducing the burden of CRDs, especially in low- and lower-middle income countries

Burden of tracheal, bronchus, and lung cancer in North Africa and Middle East countries, 1990 to 2019: Results from the GBD study 2019

ObjectiveTo provide estimates on the regional and national burden of tracheal, bronchus, and lung (TBL) cancer and its attributable risk factors from 1990 to 2019 in the North Africa and Middle East (NAME) region.Methods and materialsThe Global Burden of Disease (GBD) 2019 data were used. Disability-adjusted life years (DALYs), death, incidence, and prevalence rates were categorized by sex and age groups in the NAME region, in 21 countries, from 1990 to 2019. Decomposition analysis was performed to calculate the proportion of responsible factors in the emergence of new cases. Data are presented as point estimates with their 95% uncertainty intervals (UIs).ResultsIn the NAME region, TBL cancer caused 15,396 and 57,114 deaths in women and men, respectively, in 2019. The age-standardized incidence rate (ASIR) increased by 0.7% (95% UI -20.6 to 24.1) and reached 16.8 per 100,000 (14.9 to 19.0) in 2019. All the age-standardized indices had a decreasing trend in men and an increasing trend in women from 1990 to 2019. Turkey (34.9 per 100,000 [27.6 to 43.5]) and Sudan (8.0 per 100,000 [5.2 to 12.5]) had the highest and lowest age-standardized prevalence rates (ASPRs) in 2019, respectively. The highest and lowest absolute slopes of change in ASPR, from 1990 to 2019, were seen in Bahrain (-50.0% (-63.6 to -31.7)) and the United Arab Emirates (-1.2% (-34.1 to 53.8)), respectively. The number of deaths attributable to risk factors was 58,816 (51,709 to 67,323) in 2019 and increased by 136.5%. Decomposition analysis showed that population growth and age structure change positively contributed to new incident cases. More than 80% of DALYs could be decreased by controlling risk factors, particularly tobacco use.ConclusionThe incidence, prevalence, and DALY rates of TBL cancer increased, and the death rate remained unchanged from 1990 to 2019. All the indices and contribution of risk factors decreased in men but increased in women. Tobacco is still the leading risk factor. Early diagnosis and tobacco cessation policies should be improved

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