Pedestrian street and its effect on economic sustainability of a historical Middle Eastern city: the case of Chaharbagh Abbasi in Isfahan, Iran

Pedestrianization is an urban revitalization strategy to enhance sustainability and livability in car-oriented cities. Despite many studies in this research field, the effects of pedestrianization on the economy of cities in developing countries still need further investigation. Additionally, the impact of this strategy on the tenant mix of commercial and historical areas in Middle East countries is nebulous. To address these inadequacies, we considered Chaharbagh Abbasi street, located in the heart of Isfahan, Iran, and investigated the impact of a pedestrianization project with particular emphasis on how it affects the economic sustainability of existent commercial fabric. Pre and post-project data along with field observations and quantifications used to assess structural replacements in trade, were analyzed with SPSS and ArcGIS software. The results revealed unexpected outcomes, such as the closure of some traditional businesses (27.5%), a stagnation in sales (69%) and a decrease in job offers (84%) leading the local economy to a fragile situation. Conversely, it was found that the footfall volume increased by 64% and 73% from the retailers’ and pedestrians’ viewpoints. This evolution along with a wide opening of food and beverage stores (approximately 60%) makes the post-pedestrianization results more promising than earlier predictions. In conclusion, these findings reinforce the importance of pedestrian streets in revitalizing economic activities in historical and commercial areas from the perspective of economic sustainability. Due to the lack of similar investigations in Middle East countries, these findings can support decision-makers and urban planners to take preventive measures in preserving the diversity of individual small shops for upcoming urban rehabilitation projects in terms of pedestrianization.info:eu-repo/semantics/acceptedVersio

Analysis and modeling time headway distributions under heavy traffic flow conditions in the urban highways: case of Isfahan

The time headway of vehicles is an important microscopic traffic flow parameter which affects the safety and capacity of highway facilities such as freeways and multi-lane highways. The present paper intends to provide a report on the results of a study aimed at investigating the effect of the lane position on time headway distributions within the high levels of traffic flow. The main issue of this study is to assess the driver's behavior at different highway lanes based on a headway distribution analysis. The study was conducted in the city of Isfahan, Iran. Shahid Kharrazi six-lane highway was selected for collecting the field headway data. The under-study lanes consisted of passing and middle lanes. The appropriate models of headway distributions were selected using a methodology based on Chi-Square test for each lane. Using the selected models, the headway distribution diagrams were predicted for high levels of traffic flow in both the passing and middle lanes and the relationship between statistical criteria of the models and the driver's behaviors were analyzed. The results certify that the appropriate model for the passing lane is different than the one for the middle lane. This is because of a different behavioral operation of drivers which is affected by specific conditions of each lane. Through car-following conditions in the passing lane, a large number of drivers adopt unsafe headways. This shows high risk-ability of driver population which led to considerably differences in capacities and statistical distribution models of two lanes

CoVR: A Large-Scale Force-Feedback Robotic Interface for Non-Deterministic Scenarios in VR

We present CoVR, a novel robotic interface providing strong kinesthetic feedback (100 N) in a room-scale VR arena. It consists of a physical column mounted on a 2D Cartesian ceiling robot (XY displacements) with the capacity of (1) resisting to body-scaled users' actions such as pushing or leaning; (2) acting on the users by pulling or transporting them as well as (3) carrying multiple potentially heavy objects (up to 80kg) that users can freely manipulate or make interact with each other. We describe its implementation and define a trajectory generation algorithm based on a novel user intention model to support non-deterministic scenarios, where the users are free to interact with any virtual object of interest with no regards to the scenarios' progress. A technical evaluation and a user study demonstrate the feasibility and usability of CoVR, as well as the relevance of whole-body interactions involving strong forces, such as being pulled through or transported.Comment: 10 pages (without references), 14 pages tota

COVID-19 Associated Mucormycosis::A Review of an Emergent Epidemic Fungal Infection in 3 Era of COVID-19 Pandemic

At a time when the COVID-19's second wave is still picking up in countries like India, a number of reports describe the potential association with a rise in the number of cases of mucormycosis, commonly known as the black fungus. This fungal infection has been around for centuries and affects those people whose immunity has been compromised due to severe health conditions. In this article, we provide a detailed overview of mucormycosis and discuss how COVID-19 could have caused a sudden spike in an otherwise rare disease in countries like India. The article discusses the various symptoms of the disease, class of people most vulnerable to this infection, preventive measures to avoid the disease, and various treatments that exist in clinical practice and research to manage the disease

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

Auxetic structures in civil engineering applications: Experimental (by 3D printing) and numerical investigation of mechanical behavior

Auxetic materials are a group of metamaterials that have a negative Poisson's ratio. The most important advantage of auxetics over conventional materials is higher energy absorption. Consequently, in Civil Engineering, a wide range of applications may be considered for auxetic materials including energy absorber structural elements. In this study, two auxetic structures named re-entrant and arrowhead were selected along with the conventional honeycomb structure to investigate the effect of the negative Poisson's ratio on their mechanical behavior. These structures were produced utilizing a fused deposition modeling (FDM) 3D printer. Energy absorption was investigated numerically and experimentally. In order to increase the accuracy of the numerical study, ductile damage for the material was considered. The results showed that the ultimate forces of the re-entrant and arrowhead structures were increased by 125 % and 164 %, respectively, compared to the honeycomb structure. Furthermore, the amount of energy absorption of the re-entrant and arrowhead compared to the honeycomb structure increased by 47.4 % and 176.8 %, respectively. The rate of specific energy absorption in the two mentioned auxetic structures compared to the non-auxetic structure improved by 20.9 % and 53.5 %, respectively

Modeling a Hybrid Microgrid Using Probabilistic Reconfiguration under System Uncertainties

A novel method for a day-ahead optimal operation of a hybrid microgrid system including fuel cells, photovoltaic arrays, a microturbine, and battery energy storage in order to fulfill the required load demand is presented in this paper. In the proposed system, the microgrid has access to the main utility grid in order to exchange power when required. Available municipal waste is utilized to produce the hydrogen required for running the fuel cells, and natural gas will be used as the backup source. In the proposed method, an energy scheduling is introduced to optimize the generating unit power outputs for the next day, as well as the power flow with the main grid, in order to minimize the operational costs and produced greenhouse gases emissions. The nature of renewable energies and electric power consumption is both intermittent and unpredictable, and the uncertainty related to the PV array power generation and power consumption has been considered in the next-day energy scheduling. In order to model uncertainties, some scenarios are produced according to Monte Carlo (MC) simulations, and microgrid optimal energy scheduling is analyzed under the generated scenarios. In addition, various scenarios created by MC simulations are applied in order to solve unit commitment (UC) problems. The microgrid’s day-ahead operation and emission costs are considered as the objective functions, and the particle swarm optimization algorithm is employed to solve the optimization problem. Overall, the proposed model is capable of minimizing the system costs, as well as the unfavorable influence of uncertainties on the microgrid’s profit, by generating different scenarios