Qualitative Models of Climate Variations Impact on Crop Yields

This report presents application of machine learning methodology in modeling process. The objective is to identify and explain impact of weather variations on crop yields, and to test the approach on the agricultural and climatic data from the USA. First, separation of weather and non-weather factors is performed by trend identification- two methods of trend identification are considered. Then the importance of the attributes is assessed using information gain measure and attributes are also aggregated into seasons. Finally, four types of classification methods (support vector machines, nearestneighbors classifier and two variants of decision rules induction) are applied to the data and the results are compared and analyzed. The proposed approach differs from standard approaches to the crop yields modeling. It does not require a lot of expert knowledge, nor assume anything about the data distributions. All conclusions are drawn from data and the final model is build only from data. This approach is much simpler, however it maintains high accuracy and performanc

Comparison of machine learning algorithms used to classify the asteroids observed by all-sky surveys

Context. Multifilter photometry from large sky surveys is commonly used to assign asteroid taxonomic types and study various problems in planetary science. To maximize the science output of those surveys, it is important to use methods that best link the spectro-photometric measurements to asteroid taxonomy. Aims. We aim to determine which machine learning methods are the most suitable for the taxonomic classification for various sky surveys. Methods. We utilized five machine learning supervised classifiers: logistic regression, naive Bayes, support vector machines (SVMs), gradient boosting, and MultiLayer Perceptrons (MLPs). Those methods were found to reproduce the Bus-DeMeo taxonomy at various rates depending on the set of filters used by each survey. We report several evaluation metrics for a comprehensive comparison (prediction accuracy, balanced accuracy, F1 score, and the Matthews correlation coefficient) for 11 surveys and space missions. Results. Among the methods analyzed, multilayer perception and gradient boosting achieved the highest accuracy and naive Bayes achieved the lowest accuracy in taxonomic prediction across all surveys. We found that selecting the right machine learning algorithm can improve the success rate by a factor of >2. The best balanced accuracy (similar to 85% for a taxonomic type prediction) was found for the Visible and Infrared Survey telescope for Astronomy (VISTA) and the ESA Euclid mission surveys where broadband filters best map the 1 mu m and 2 mu m olivine and pyroxene absorption bands. Conclusions. To achieve the highest accuracy in the taxonomic type prediction based on multifilter photometric measurements, we recommend the use of gradient boosting and MLP optimized for each survey. This can improve the overall success rate even when compared with naive Bayes. A merger of different datasets can further boost the prediction accuracy. For the combination of the Legacy Survey of Space and Time and VISTA survey, we achieved 90% for the taxonomic type prediction.Peer reviewe

Age as a Risk Factor for Severe Manifestations and Fatal Outcome of Falciparum Malaria in European Patients: Observations from TropNetEurop and SIMPID Surveillance Data

Previous studies have indicated that age is a risk factor for severe falciparum malaria in nonimmune patients. The objectives of this study were to reevaluate previous findings with a larger sample and to find out how strongly clinical outcomes for elderly patients differ from those for younger patients. Results of adjusted analyses indicated that the risks of death due to falciparum malaria, of experiencing cerebral or severe disease in general, and of hospitalization increased significantly with each decade of life. The case-fatality rate was almost 6 times greater among elderly patients than among younger patients, and cerebral complications occurred 3 times more often among elderly patients. Antimalarial chemoprophylaxis was significantly associated with a lower case-fatality rate and a lower frequency of cerebral complications. Women were more susceptible to cerebral complications than were men. Our study provides evidence that falciparum malaria is more serious in older patients and demonstrates that clinical surveillance networks are capable of providing quality data for investigation of rare events or disease

Distribution of Mycobacterium ulcerans in Buruli Ulcer Endemic and Non-Endemic Aquatic Sites in Ghana

Mycobacterium ulcerans, the causative agent of Buruli ulcer, is an emerging environmental bacterium in Australia and West Africa. The primary risk factor associated with Buruli ulcer is proximity to slow moving water. Environmental constraints for disease are shown by the absence of infection in arid regions of infected countries. A particularly mysterious aspect of Buruli ulcer is the fact that endemic and non-endemic villages may be only a few kilometers apart within the same watershed. Recent studies suggest that aquatic invertebrate species may serve as reservoirs for M. ulcerans, although transmission pathways remain unknown. Systematic studies of the distribution of M. ulcerans in the environment using standard ecological methods have not been reported. Here we present results from the first study based on random sampling of endemic and non-endemic sites. In this study PCR-based methods, along with biofilm collections, have been used to map the presence of M. ulcerans within 26 aquatic sites in Ghana. Results suggest that M. ulcerans is present in both endemic and non-endemic sites and that variable number tandem repeat (VNTR) profiling can be used to follow chains of transmission from the environment to humans. Our results suggesting that the distribution of M. ulcerans is far broader than the distribution of human disease is characteristic of environmental pathogens. These findings imply that focal demography, along with patterns of human water contact, may play a major role in transmission of Buruli ulcer

Ecology and Transmission of Buruli Ulcer Disease: A Systematic Review

Buruli ulcer is a neglected emerging disease that has recently been reported in some countries as the second most frequent mycobacterial disease in humans after tuberculosis. Cases have been reported from at least 32 countries in Africa (mainly west), Australia, Southeast Asia, China, Central and South America, and the Western Pacific. Large lesions often result in scarring, contractual deformities, amputations, and disabilities, and in Africa, most cases of the disease occur in children between the ages of 4–15 years. This environmental mycobacterium, Mycobacterium ulcerans, is found in communities associated with rivers, swamps, wetlands, and human-linked changes in the aquatic environment, particularly those created as a result of environmental disturbance such as deforestation, dam construction, and agriculture. Buruli ulcer disease is often referred to as the “mysterious disease” because the mode of transmission remains unclear, although several hypotheses have been proposed. The above review reveals that various routes of transmission may occur, varying amongst epidemiological setting and geographic region, and that there may be some role for living agents as reservoirs and as vectors of M. ulcerans, in particular aquatic insects, adult mosquitoes or other biting arthropods. We discuss traditional and non-traditional methods for indicting the roles of living agents as biologically significant reservoirs and/or vectors of pathogens, and suggest an intellectual framework for establishing criteria for transmission. The application of these criteria to the transmission of M. ulcerans presents a significant challenge

Differentiation of Listeria monocytogenes on the basis of hemolytic and phosphatidylinositol specific phospholipase C activity and by PCR method

The possibility of differentiation of L.monocytogenes from other Listeria species on the basis of hemolytic activity, the production of phosphatidylinositol-specific phospholipase C (PI-PLC) and the polymerase chain reaction (PCR) for the amplification of a DNA fragment of listeriolysine O (hly A) gene was compared. The screening of Listeria colonies for PI-PLC activity allowed to distinguish the pathogenic for humans L.monocytogenes bacteria from the majority of non-pathogenic Listeria spp. The amplification of DNA from Listeria lysates with two primers selected in area of the hly A gene made possible the differentiation of L.monocytogenes from other Listeria species, including hemolytic L.ivanovii and L.seeligeri bacteria as well as hemolytic or PI-PLC positive L.innocua strains.Żywność zanieczyszczona Listeria monocytogenes byía notowana jako źródło zakażeń pokarmowych o charakterze epidemicznym w krajach w Europie i Ameryce Północnej. W związku z tym koniecznością się stalo opracowanie szybkich i czuîych testów wykrywania i identyfikacji pałeczek L. monocytogenes. W pracy porównano przydatność trzech testów do odróżniania chorobotwórczych dla człowieka bakterii L. monocytogenes od innych niepatogennych gatunków Listeria. Uzyskane wyniki wskazują, na niewielką przydatność oceny aktywności hemolitycznej dla różnicowania szczepów L. monocytogenes od niechorobotwórczych dla ludzi szczepów L. ivanovii, L. seeligeri oraz L. innocua. Różnicowanie takich szczepów w oparciu o aktywność fosfolipazy C fosfatydyloinozytolu wykazuje wyższą specyficzność. Cechę taką wykazywały wszystkie badane szczepy L. monocytogenes i tylko jeden szczep L. innocua spośród 9 niepatogennych szczepów Listeria. Amplifikacja fragmentu DNA w obrębie genu dla listeriolizyny O (hly A) L. monocytogenes, pozwoliła odróżnić wszystkie (18) szczepy L. monocytogenes od niepatogennych dla człowieka bakterii L. ivanovii, L. innocua, L. seeligeri, L. welshimeri oraz L. grayi. Trawienie produktu amplifikacji DNA enzymem Taq I, pozwoliło na wyodrębnienie dwóch typów w obrębie grupy badanych szczepów L. monocytogenes