Plastic debris on Pacific Islands: Ecological and health implications

© 2019 Plastic debris is a worldwide problem. This is particularly acute in the Pacific region, where its scale is a reason for serious concerns. There is an obvious need for studies to assess the extent to which plastic debris affects the Pacific. Therefore, this research aims to address this need by undertaking a systematic assessment of the ecological and health impacts of plastic debris on Pacific islands. Using pertinent historical qualitative and quantitative data of the distribution of plastic debris in the region, this study identified pollution and contamination trends and risks to ecosystems, and suggests some measures which may be deployed to address the identified problems. The study illustrates the fact that Pacific Island States are being disproportionately affected by plastic, and reiterates that further studies and integrated strategies are needed, involving public education and empowerment, governmental action, as well as ecologically sustainable industry leadership. It is also clear that more research is needed in respect of developing alternatives to conventional plastic, by the production of bio-plastic, i.e. plastic which is produced from natural (e.g. non-fossil fuel-based sources) materials, and which can be fully biodegradable

Using the jet stream for sustainable airship and balloon transportation of cargo and hydrogen

© 2019 The Author(s) The maritime shipping sector is a major contributor to CO2 emissions and this figure is expected to rise in coming decades. With the intent of reducing emissions from this sector, this research proposes the utilization of the jet stream to transport a combination of cargo and hydrogen, using airships or balloons at altitudes of 10–20 km. The jet streams flow in the mid-latitudes predominantly in a west–east direction, reaching an average wind speed of 165 km/h. Using this combination of high wind speeds and reliable direction, hydrogen-filled airships or balloons could carry hydrogen with a lower fuel requirement and shorter travel time compared to conventional shipping. Jet streams at different altitudes in the atmosphere were used to identify the most appropriate circular routes for global airship travel. Round-the-world trips would take 16 days in the Northern Hemisphere and 14 in the Southern Hemisphere. Hydrogen transport via the jet stream, due to its lower energy consumption and shorter cargo delivery time, access to cities far from the coast, could be a competitive alternative to maritime shipping and liquefied hydrogen tankers in the development of a sustainable future hydrogen economy

Spatio-temporal analysis of oil spill impact and recovery pattern of coastal vegetation and wetland using multispectral satellite Landsat 8-OLI imagery and machine learning models

© 2020, by the authors. Oil spills are a global phenomenon with impacts that cut across socio-economic, health, and environmental dimensions of the coastal ecosystem. However, comprehensive assessment of oil spill impacts and selection of appropriate remediation approaches have been restricted due to reliance on laboratory experiments which offer limited area coverage and classification accuracy. Thus, this study utilizes multispectral Landsat 8-OLI remote sensing imagery and machine learning models to assess the impacts of oil spills on coastal vegetation and wetland and monitor the recovery pattern of polluted vegetation and wetland in a coastal city. The spatial extent of polluted areas was also precisely quantified for effective management of the coastal ecosystem. Using Johor, a coastal city in Malaysia as a case study, a total of 49 oil spill (ground truth) locations, 54 non-oil-spill locations and Landsat 8-OLI data were utilized for the study. The ground truth points were divided into 70% training and 30% validation parts for the classification of polluted vegetation and wetland. Sixteen different indices that have been used to monitor vegetation and wetland stress in literature were adopted for impact and recovery analysis. To eliminate similarities in spectral appearance of oil-spill-affected vegetation, wetland and other elements like burnt and dead vegetation, Support Vector Machine (SVM) and Random Forest (RF) machine learning models were used for the classification of polluted and nonpolluted vegetation and wetlands. Model optimization was performed using a random search method to improve the models' performance, and accuracy assessments confirmed the effectiveness of the two machine learning models to identify, classify and quantify the area extent of oil pollution on coastal vegetation and wetland. Considering the harmonic mean (F1), overall accuracy (OA), User's accuracy (UA), and producers' accuracy (PA), both models have high accuracies. However, the RF outperformed the SVM with F1, OA, PA and UA values of 95.32%, 96.80%, 98.82% and 95.11%, respectively, while the SVM recorded accuracy values of F1 (80.83%), OA (92.87%), PA (95.18%) and UA (93.81%), respectively, highlighting 1205.98 hectares of polluted vegetation and 1205.98 hectares of polluted wetland. Analysis of the vegetation indices revealed that spilled oil had a significant impact on the vegetation and wetland, although steady recovery was observed between 2015-2018. This study concludes that Chlorophyll Vegetation Index, Modified DifferenceWater Index, Normalized Difference Vegetation Index and Green Chlorophyll Index vegetation indices are more sensitive for impact and recovery assessment of both vegetation and wetland, in addition to Modified Normalized Difference Vegetation Index for wetlands. Thus, remote sensing and Machine Learning models are essential tools capable of providing accurate information for coastal oil spill impact assessment and recovery analysis for appropriate remediation initiatives

Investigation of Air Pollution Impact on Kinta River Water Quality at a Tropical Region

Critical air quality levels lead to an unhealthy environment which disrupts physical activities and human health. Wet deposition of air pollutants might cause a high concentration of water pollution due to rain water washout of nitrate and particulate matter (PM). This study aimed to investigate the impacts of air pollutants deposition on river water quality in Malaysia. The methodology involved in the analysis of secondary data (January to December 2013) for air quality and river water quality using factor, correlation, and regression. Parameters of air quality were PM10, Nitrate (NO3), ozone (O3) and temperature while water quality data were turbidity, Nitrate and PM10 (Ca, As, Hg, Cd, Cr, Pb, Zn, Cl, Fe, K, Mg, Na). The results show that there were positive correlations between air quality indicators and Kinta river water quality parameters. Correlation matrix shows that in terms of turbidity, air and water data were having 96% similarities. Regarding Nitrate concentrations, air and water records had only 30% of correlation matrix, which can be due to other sources of Nitrate which was agriculture activities near Kinta River. The factor analysis results showed that PM was the main contributor to river water quality particles with 94%. © 2020 Published under licence by IOP Publishing Ltd

A Scalable Algorithm for Interpreting DNA Sequence and Predicting the Response of Killer T-Cells in Systemic Lupus Erythematosus Patients

The incidence and prevalence of SLE in North America are 23.2 and 241 per 100,000 people per year respectively while the incidence in Africa is 0.3 per 100,000 people per year. The study aims to predict the autoimmune response of killer T-cells in a patient suffering from Systemic Lupus Erythematosus by searching for variations in genes regulating the activities of Killer T cells. An approximate matching algorithm applying the Boyer-Moore Algorithm for the matching algorithm. Nucleotide sequences of each of the genes liked to Killer T-cells in reference human genome to DNA sequences of SLE patients. The threshold on all single nucleotide polymorphisms (SNPs) is set to 10% of the nucleotide sequence length of the gene. For 50% of susceptibility genes with no match the patient is susceptible. Sixteen (16) patients show that they are all guaranteed to manifest autoimmune Killer T-cells. The algorithm can predict the response of killer T-cells and improve the early detection and treatment of SLE patients. A similar approach can be used for genetically linked diseases like cancer.&nbsp

Promotion of healthy nutrition in clinical practice: a cross-sectional survey of practices and barriers among physiotherapists in southeast Nigeria

AbstractBackgroundHealthy diet counselling is an important concept in health promotion. Physiotherapists are well positioned to initiate or support healthy nutrition in addition to physical activity counselling, in routine patient consultation.ObjectiveTo determine the practices about and barriers to diet counselling practices among physiotherapists in Southeast Nigeria.MethodsIn this cross-sectional survey, a total of 140 questionnaires were distributed among physiotherapists.ResultsOverall, 103 physiotherapists responded. Physiotherapists are confident and consider the incorporation of dietary counselling very important and of high priority in their daily clinical work. They, however, assessed and counselled on dietary status opportunistically in patients. Notwithstanding, physiotherapists believed that the diet counselling they give could be effective in helping patients change their unhealthy dieting practices. Patients were also amenable to physiotherapists advocating on diet issues as part of their consultation. Several barriers to incorporating diet counselling into physiotherapy practice were identified, including lack of access to a dietician/health promotion staff/counsellors, lack of proper patient education materials, lack of expertise in relation to dietary risk factors' assessment and management, and uncertainty about what dietary services to provide.ConclusionAlthough physiotherapists consider it important to incorporate diet counselling in their daily clinical practice, development and implementation of strategies to improve physiotherapists' diet counselling knowledge, competence, skills, and practice are warranted

Baseline epidemiology and associated dog ecology study towards stepwise elimination of rabies in Kwara state, Nigeria

Understanding domestic dog population dynamics and ecology is crucial to any effective rabies control program. This study was conducted as part of the baseline epidemiological studies necessary for the establishment of the Kwara Rabies Rapid Alert System "KRRAS". This study aimed to determine the dog population structure of Kwara State by assessing the dog ownership, vaccination status, and prevalence of dog bites. A total of 1460 questionnaires were administered to respondents in the three senatorial zones of the state using Open Data Kit (ODK) between June 2019 to January 2020. Of the 1460 households surveyed, 293 (20.1 %) owned at least one dog with an average of 2.25 dogs per household. The male to female ratio was 1.9:1 and 79.3 % (n = 523/659) of the owned dogs were local breeds. A total of 785 dogs was enumerated (659 dogs from 293 households and 126 free-roaming dogs) and 7811 persons which resulted in a dog-human ratio of 1:9.95. The estimated dog population is 376,789 (95 % CI: 343,700 - 379,878). Only 31 % (n = 204/659) of households vaccinated their dogs against rabies. The prevalence of dog-bite was 13 % (n = 193/1460) of which only 27 % of the victims (n = 61/225) received post-exposure prophylaxis (PEP). Dog ownership was significantly impacted by the ethnicity of respondents. Hausa (OR: 3.76; 95 % CI: 1.15-12.4; p &lt; 0.001) and Nupe (OR: 4.48; 95 % CI: 1.77-11.33; p &lt; 0.001) respondents owned dogs than Yoruba respondents. The rabies vaccination status of owned dogs was significantly impacted by the level of education (OR: 5.03; 95 % CI: 1.50-16.83; p &lt; 0.001); history of previous dog bite incidents (OR: 1.74; 95 % CI: 0.95-3.17; p &lt; 0.001); the breed of the dog with exotic dogs being more vaccinated (OR: 2.79: 95 % 0.64-12.05; p &lt; 0.001). Similarly, Male dogs (OR: 1.49, 95 % 1.03-2.86; p &lt; 0.001) and partially confined dogs (OR: 1.09, 95 % 0.45-2.11, p &lt; 0.001) were found to be vaccinated against rabies. The results of the study showed low dog vaccination coverage, and high number of free roaming dogs. Hence, a threat to public health. The low dog vaccination coverage is below the 70-80 % target recommended for herd immunity by the World Health Organization.</p

A comparative study of approaches towards energy efficiency and renewable energy use at higher education institutions

© 2019 Elsevier Ltd The potential for energy efficiency and for the deployment of renewable energy at universities is substantial, and they represent promising ways to meet an institution's energy needs on the one hand, without a large climate burden on the other. However, in order to achieve successful investment and results, it is imperative to understand the level of current commitment to energy actions. Therefore, this paper investigates the level of engagement in energy efficiency measures of a sample of 50 higher education institutions from round the world, and identifies which types of renewable energy are being used to date. Results show that in more than half of the universities only a small portion of energy consumption comes from renewable sources (1%–20%) and solar/photovoltaics is the most used source (70%). Investment in energy efficiency is more common in the sample, with 54% of the universities reporting higher levels of engagement, mainly in buildings (78%) and equipment/machineries (56%). Departing from the assumption that sustainable energy use is a pre-condition for campuses to pursue sustainability, the paper identifies current deficiencies and discusses improvements in this key area, with experiences which may be replicable elsewhere

Seroprevalence of hepatitis C in type 2 diabetes: evidence for a positive association

<p>Abstract</p> <p>Background</p> <p>There is a growing body of literature on the relationship of Hepatitis C virus infection (HCV) and type 2 diabetes mellitus (T2DM). However, there are certain gaps in literature and the data is inconclusive. This study was, therefore, carried out to determine the prevalence of HCV infection in diabetic patients and to elucidate the presence of any possible relationship between HCV and T2DM in this region.</p> <p>Methods</p> <p>Serologic testing for anti-HCV antibody was done on a sample of 3000 individuals with T2DM visiting Diabetes Clinic of Nishtar Medical College Hospital, Multan and 10,000 volunteer blood donors visiting blood bank of the same hospital during the study period using Accurate rapid immunochromatographic kits which was later confirmed by using Chemelex S.A third generation ELISA kit for positive cases. Data about various variables was collected from diabetic patients using a structured questionnaire after taking informed consent.</p> <p>Results</p> <p>Prevalence rate of 13.7% for HCV infection was recorded among subjects having T2DM with seropositivity rate of 4.9% among the control group of volunteer blood donors without diabetes. The patients with T2DM were more likely to have HCV infection as compared to the control group (OR = 3.03, 95%CI = 2.64-3.48, p = 0.001). Diabetic patients with age above 55 years had higher prevalence rate as compared to younger individuals. Male patients had significantly high seropositivity as compared to female patients (15.3% vs. 12.4%, p = 0.02). Those with duration of diabetes 11 years and above and the ones with good glycemic control had higher seroprevalence rates of 18.2% and 18.7% respectively. There was no statistically significant difference among subjects when the distribution of HCV was studied on the basis of marital status, locality, or family history of diabetes.</p> <p>Conclusions</p> <p>The results show that there is a strong association between HCV and T2DM in the region as evident from significantly higher prevalence of HCV infection in diabetics as compared to the control group in the present study.</p