Models Development for Asphalt Pavement Performance Index in Different Climate Regions Using Soft Computing Techniques

The Pavement Condition Index (PCI) is one of the most critical pavement performance indicators and ride quality. This study aims to develop PCI models based on pavement distress parameters using conventional technique and artificial neural network (ANN) technique across two climate regions in the U.S. and Canada. The long-term pavement performance (LTPP) database was used to obtain pavement distress data, including pavement age, rutting, fatigue cracking, block cracking, longitudinal cracking, transverse cracking, potholes, patching, bleeding, and ravelling, as input variables for predicting PCI. Forty-three flexible pavement segments were considered with 333 observations. The type, severity, and extent of surface damage and the PCI were determined for each pavement segment. Two modelling techniques were conducted to predict the PCI, namely, multiple linear regression (MLR) and artificial neural network (ANN). The coefficient of determination (R2), Root mean squared error (RMSE), and mean absolute error (MAE) were used to examine the performance of the two techniques adopted in this study. The models' results determined that both ANN and MLR models could predict PCI with high accuracy; ANN models were more accurate and efficient. ANN provided the highest accuracy in predicting PCI of pavement for wet and wet no-freeze climate regions, with R2 values of 99.8%, 98.3 %: RMSE values of 0.44%, 1.413%, and MAE values of 0.44%, 1.022%, respectively. Whereas in the MLR method, R2 values of 86.8% and 89.4%: RMSE values of 7.195%, 7.324%, and MAE values of 5.616%, 5.79% for wet and wet no freeze climate regions, respectively

Analysis of Human Gait Cycle with Body Equilibrium based on leg Orientation

Gait analysis identifies the posture during movement in order to provide the correct actions for a normal gait. A person\u27s gait may differ from others and can be recognized by specific patterns. Healthy individuals exhibit normal gait patterns, while lower limb amputees exhibit abnormal gait patterns. To better understand the pitfalls of gait, it is imperative to develop systems capable of capturing the gait patterns of healthy individuals. The main objective of this research was to introduce a new concept in gait analysis by computing the static and dynamic equilibrium in a real-world environment. A relationship was also presented among the parameters stated as static \& dynamic equilibrium, speed, and body states. A sensing unit was installed on the designed metal-based leg mounting assembly on the lateral side of the leg. An algorithm was proposed based on two variables: the position of the leg in space and the angle of the knee joint measured by an IMU sensor and a rotary encoder. It was acceptable to satisfy the static conditions when the body was in a fixed position and orientation, whether lying down or standing. While walking and running, the orientation is determined by the position and knee angle variables, which fulfill the dynamic condition. High speed reveals a rapid change in orientation, while slow speed reveals a slow change in orientation. The proposed encoder-based feedback system successfully determined the flexion at 47$^\circ$, extension at 153$^\circ$, and all seven gait cycle phases were recognized within this range of motion. Body equilibrium facilitates individuals when they are at risk of falling or slipping

Estimation of biocidal potential of desert phytopowders for the management of citrus canker

Citrus is one of the most important fruit crops, throughout the world. It is a rich source of antioxidants and vitamin C. Citrus canker is a potential threat to its successful production. In current study, ten desert phytopowders including Xanthium strumarium, Dipterygium galucun, Leptadenia pyrotechnica, Haloxylon recurvum, Suaeda fruticosa, Salsola baryosma, Citrulus colocynthis, Abutilon indicum, Aerva javanica, and Calotropis procera at three different concentrations (5.0, 7.5 and 10.0%) were evaluated under in vitro conditions against Xanthomonas citri pv. citri. Among all phytopowders, X. strumarium and S. fruticosa, showed maximum inhibition zone (40 mm) followed by S. baryosma (38.50 mm) C. colocynthis (37 mm), Abutilon indicum (34 mm), H. recurvum (32 mm), D. galucun (30.5 mm), A. javanica, (29.50 mm), L. pyrotechnica, (29.5 mm) and C. procera (28 mm) as compared to control. Then, effective phytopowders were applied under greenhouse and field conditions @ 5.0, 7.5 and 10.0% against citrus canker. Combination of X. strumarium + S. baryosma showed minimum disease severity (22%) followed by X. strumarium (26%), X. strumarium + S. fruticosa (27%), S. fruticosa (27%), X. strumarium + S. baryosma (27%), and S. baryosma (29%) as compared to control. While in field experiment, the combination of X. strumarium + S. fruticosa showed significant results with minimum disease severity (32%) followed by S. fruticosa + S. baryosma (32%), X. strumarium + S. baryosma (33%), S. baryosma (35%), X. strumarium (36%) and S. fruticosa (36%) as compared to control. It is concluded that application of X. strumarium + S. baryosma phytopowders will be helpful for farmers to combat citrus canker

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication

Application of Artificial neural network technique for prediction of pavement roughness as a performance indicator

One of the most important and widely accepted pavement performance and ride quality indicators is the International Roughness Index (IRI). This study investigates the combined effect of pavement distress on flexible pavement performance in two climate regions (wet freeze and wet freeze) in the U.S. and Canada. The long-term pavement performance (LTPP) database was used to obtain pavement distress data. Data from forty-three of the LTPP pavement sections (333 observations) with no previous maintenance were collected. The proposed models predict the IRI as a function of pavement distress variables, namely the pavement age, rutting, fatigue cracking, block cracking, longitudinal cracking, transverse cracking, potholes, patching, bleeding, and ravelling. After the data were collected, modelling was conducted to predict IRI using two techniques: multiple linear regression (MLR) and artificial neural network (ANN). The coefficient of determination (R2), root mean squared error (RMSE) and mean absolute error (MAE) were used to examine the performance of the two techniques adopted in this study. The models' results revealed that both ANN and MLR models could predict IRI with good accuracy. The MLR models yielded the R2 values of 77.7% and 89.3%, whereas the ANN models resulted in the R2 values of 99.1% and 97.5% for wet freeze and wet no freeze climate regions, respectively. As a result, ANN models are more accurate and efficient than MLR models

The impact of biomass energy consumption on pollution: evidence from 80 developed and developing countries

The aim of this research is to explore the effect of biomass energy consumption on CO2 emissions in 80 developed and developing countries. To achieve robustness, the system generalised method of moment was used and several control variables were incorporated into the model including real GDP, fossil fuel consumption, hydroelectricity production, urbanisation, population, foreign direct investment, financial development, institutional quality and the Kyoto protocol. Relying on the classification of the World Bank, the countries were categorised to developed and developing countries. We also used a dynamic common correlated effects estimator. The results consistently show that biomass energy as well as fossil fuel consumption generate more CO2 emissions. A closer look at the results show that a 100% increase in biomass consumption (tonnes per capita) will increase CO2 emissions (metric tons per capita) within the range of 2 to 47%. An increase of biomass energy intensity (biomass consumption in tonnes divided by real gross domestic product) of 100% will increase CO2 emissions (metric tons per capita) within the range of 4 to 47%. An increase of fossil fuel consumption (tonnes of oil equivalent per capita) by 100% will increase CO2 emissions (metric tons per capita) within the range of 35 to 55%. The results further show that real GDP urbanisation and population increase CO2 emissions. However, hydroelectricity and institutional quality decrease CO2 emissions. It is further observed that financial development, foreign direct investment and openness decrease CO2 emissions in the developed countries, but the opposite results are found for the developing nations. The results also show that the Kyoto Protocol reduces emission and that Environmental Kuznets Curve exists

Technoeconomic Feasibility of Hydrogen Production from Waste Tires with the Control of CO2Emissions

The worldwide demand for energy is increasing significantly, and the landfill disposal of waste tires and their stockpiles contributes to huge environmental impacts. Thermochemical recycling of waste tires to produce energy and fuels is an attractive option for reducing waste with the added benefit of meeting energy needs. Hydrogen is a clean fuel that could be produced via the gasification of waste tires followed by syngas processing. In this study, two process models were developed to evaluate the hydrogen production potential from waste tires. Case 1 involves three main processes: The steam gasification of waste tires, water gas shift, and acid gas removal to produce hydrogen. On the other hand, case 2 represents the integration of the waste tire gasification system with the natural gas reforming unit, where the energy from the gasifier-derived syngas can provide sufficient heat to the steam methane reforming (SMR) unit. Both models were also analyzed in terms of syngas compositions, H2production rate, H2purity, overall process efficiency, CO2emissions, and H2production cost. The results revealed that case 2 produced syngas with a 55% higher heating value, 28% higher H2production, 7% higher H2purity, and 26% lower CO2emissions as compared to case 1. The results showed that case 2 offers 10.4% higher process efficiency and 28.5% lower H2production costs as compared to case 1. Additionally, the second case has 26% lower CO2-specific emissions than the first, which significantly enhances the process performance in terms of environmental aspects. Overall, the case 2 design has been found to be more efficient and cost-effective compared to the base case design

Technoeconomic Feasibility of Hydrogen Production from Waste Tires with the Control of CO2Emissions

The worldwide demand for energy is increasing significantly, and the landfill disposal of waste tires and their stockpiles contributes to huge environmental impacts. Thermochemical recycling of waste tires to produce energy and fuels is an attractive option for reducing waste with the added benefit of meeting energy needs. Hydrogen is a clean fuel that could be produced via the gasification of waste tires followed by syngas processing. In this study, two process models were developed to evaluate the hydrogen production potential from waste tires. Case 1 involves three main processes: The steam gasification of waste tires, water gas shift, and acid gas removal to produce hydrogen. On the other hand, case 2 represents the integration of the waste tire gasification system with the natural gas reforming unit, where the energy from the gasifier-derived syngas can provide sufficient heat to the steam methane reforming (SMR) unit. Both models were also analyzed in terms of syngas compositions, H2production rate, H2purity, overall process efficiency, CO2emissions, and H2production cost. The results revealed that case 2 produced syngas with a 55% higher heating value, 28% higher H2production, 7% higher H2purity, and 26% lower CO2emissions as compared to case 1. The results showed that case 2 offers 10.4% higher process efficiency and 28.5% lower H2production costs as compared to case 1. Additionally, the second case has 26% lower CO2-specific emissions than the first, which significantly enhances the process performance in terms of environmental aspects. Overall, the case 2 design has been found to be more efficient and cost-effective compared to the base case design