SOCIO-ENVIRONMENTAL FACTORS ASSOCIATED WITH THE DISTRIBUTION OF DRACUNCULUS MEDINENSIS (GUINEA WORM DISEASE) AND SUGGESTED METHODS FOR CONTROL, IBARAPA, NIGERIA, 1982 (AFRICA)

A population-based cross-sectional survey of socio-environmental factors associated with the prevalence of Dracunculus medinensis (guinea worm disease) was conducted in Idere, a rural agricultural community in Ibarapa, Oyo state, Nigeria, during 1982.^ The epidemiologic data were collected by household interview of all 501 households. The environmental data were collected by analysis of water samples collected from all domestic water sources and rainfall records.^ The specific objectives of this research were to: (a) Describe the prevalence of guinea worm disease in Idere during 1982 by age, sex, area of residence, drinking water source, religion and weekly amount of money spent by the household to collect potable drinking water. (b) Compare the characteristics of cases with non-cases of guinea worm in order to identify factors associated with high risk of infection. (c) Investigate domestic water sources for the distribution of Cyclops. (d) Determine the extent of potable water shortage with a view to identifying factors responsible for such shortage in the community. (e) Describe the effects of guinea worm on school attendance during 1980/1982 school years by class and location of school from piped water supply.^ The findings of this research indicate that during 1982, 31.8 percent of Idere's 6,527 residents experienced guinea worm infection, with higher prevalence of infection recorded in males in their most productive years and females in their teenage years. The role of sex and age to risk of higher infection rate was explained in the context of water related exposure and water intake due to dehydration from physical occupational actitives of subgroups.^ Potable water available to residents was considerably below the minimum recommended by WHO for tropical climates, with sixty-eight percent of water needs of the residents coming from unprotected surface water which harbour Cyclops, the obligatory intermediate host of Dracunculus medinensis. An association was found between periods of relative high density of Cyclops in domestic water and rainfall.^ Impact of guinea worm infection on educational activities was considerable and its implications were discussed, including the implications of the research findings in relation to control of guinea worm disease in Ibarapa. ^

Comparison of machine learning approaches and statistical methods for estimation of airborne chemical exposures

Accurate quantitative estimation of exposure using retrospective data has been one of the most challenging tasks in the exposure assessment field. To improve these estimates, some models have been developed using published exposure databases with their corresponding exposure determinants. These models are designed to be applied to reported exposure determinants obtained from study subjects or exposure levels assigned by an industrial hygienist, so quantitative exposure estimates can be obtained. ^ In an effort to improve the prediction accuracy and generalizability of these models, and taking into account that the limitations encountered in previous studies might be due to limitations in the applicability of traditional statistical methods and concepts, the use of computer science- derived data analysis methods, predominantly machine learning approaches, were proposed and explored in this study. ^ The goal of this study was to develop a set of models using decision trees/ensemble and neural networks methods to predict occupational outcomes based on literature-derived databases, and compare, using cross-validation and data splitting techniques, the resulting prediction capacity to that of traditional regression models. Two cases were addressed: the categorical case, where the exposure level was measured as an exposure rating following the American Industrial Hygiene Association guidelines and the continuous case, where the result of the exposure is expressed as a concentration value. Previously developed literature-based exposure databases for 1,1,1 trichloroethane, methylene dichloride and, trichloroethylene were used. ^ When compared to regression estimations, results showed better accuracy of decision trees/ensemble techniques for the categorical case while neural networks were better for estimation of continuous exposure values. Overrepresentation of classes and overfitting were the main causes for poor neural network performance and accuracy. Estimations based on literature-based databases using machine learning techniques might provide an advantage when they are applied to other methodologies that combine `expert inputs' with current exposure measurements, like the Bayesian Decision Analysis tool. The use of machine learning techniques to more accurately estimate exposures from literature-based exposure databases might represent the starting point for the independence from the expert judgment.^

Phosphorus and Potassium Rates and Placement Methods for Corn and Soybean Managed with No-till or Tillage

No-till management for corn and soybean results in little or no incorporation of crop residues and fertilizer with soil. Subsurface banding phosphorus (P) and potassium (K) fertilizers with planter attachments could be more effective than broadcast fertilization, because in no-till with broadcast fertilizer, both nutrients accumulate at or near the soil surface. A long-term study was initiated in 1994 at the ISU Northwest Research Farm to evaluate P and K fertilizer placement for corn and soybean managed with no-till and chiselplow tillage.

Calibration and application of B/Ca, Cd/Ca, and d11B in Neogloboquadrina pachyderma (sinistral)

The North Atlantic and Norwegian Sea are prominent sinks of atmospheric CO2 today, but their roles in the past remain poorly constrained. In this study, we attempt to use B/Ca and d11B ratios in the planktonic foraminifera Neogloboquadrina pachyderma (sinistral variety) to reconstruct subsurface water pH and pCO2 changes in the polar North Atlantic during the last deglaciation. Comparison of core-top results with nearby hydrographic data shows that B/Ca in N. pachyderma (s) is mainly controlled by seawater [B(OH)4]?/[HCO3]? with a roughly constant partition coefficient (KD =([B/Ca]of CaCO3)/([B(OH)4]-/[HCO3]-)of seawater) of 1.48 ± 0.15 * 10**-3 (2sigma), and d11B in this species is offset below d11B of the borate in seawater by 3.38 ± 0.71 per mil (2sigma). These values represent our best estimates with the sparse available hydrographic data close to our core-tops. More culturing and sediment trap work is needed to improve our understanding of boron incorporation into N. pachyderma (s). Application of a constant KD of 1.48 * 10**-3 to high resolution N. pachyderma (s) B/Ca records from two adjacent cores off Iceland shows that subsurface pCO2 at the habitat depth of N. pachyderma (s) (~50 m) generally followed the atmospheric CO2 trend but with negative offsets of ~10-50 ppmv during 19-10 ka. These B/Ca-based reconstructions are supported by independent estimates from low-resolution d11B measurements in the same cores. We also calibrate and apply Cd/Ca in N. pachyderma (s) to reconstruct nutrient levels for the same down cores. Like today's North Atlantic, past subsurface pCO2 variability off Iceland was significantly correlated with nutrient changes that might be linked to surface nutrient utilization and mixing within the upper water column. Because surface pCO2 (at 0 m water depth) is always lower than at deeper depths and if the application of a constant KD is valid, our results suggest that the polar North Atlantic has remained a CO2 sink during the calcification seasons of N. pachyderma (s) over the last deglaciation.

An environmental magnetic study, sedimentological and numerical methods around Tauranga Harbour, New Zealand

Magnetic iron minerals are widespread and indicative sediment constituents in estuarine, coastal and shelf systems. We combine environmental magnetic, sedimentological and numerical methods to identify magnetite-enriched placer-like zones in a complex coastal system and delineate their formation mechanisms. Magnetic susceptibility and remanence measurements on 245 surficial sediment samples collected in and around Tauranga Harbour, the largest barrier-enclosed tidal estuary of New Zealand, reveal several discrete enrichment zones controlled by local hydrodynamic conditions. Active magnetite enrichment takes place in tidal channels, which feed into two coast-parallel nearshore magnetite-enriched belts centered at water depths of 6-10 m and 10-20 m. A close correlation between magnetite content and magnetic grain size was found, where higher susceptibility values are associated within coarser magnetic crystal sizes. Two key mechanisms for magnetite enrichment are identified. First, tide-induced residual currents primarily enable magnetite enrichment within the estuarine channel network. A coast-parallel, fine sand magnetite enrichment belt in water depths of less than 10 m along the barrier island has a strong decrease in magnetite content away from the southern tidal inlet and is apparently related to active coast-parallel transport combined with mobilizing surf zone processes. A second, less pronounced, but more uniform magnetite enrichment belt at 10-20 m water depth is composed of non-mobile, medium-coarse-grained relict sands, which have been reworked during post-glacial sea level transgression. We demonstrate the potential of magnetic methods to reveal and differentiate coastal magnetite enrichment patterns and investigate their formative mechanisms.

Enhancing Activity Recognition by Fusing Inertial and Biometric Information

Activity recognition is an active research field nowadays, as it enables the development of highly adaptive applications, e.g. in the field of personal health. In this paper, a light high-level fusion algorithm to detect the activity that an individual is performing is presented. The algorithm relies on data gathered from accelerometers placed on different parts of the body, and on biometric sensors. Inertial sensors allow detecting activity by analyzing signal features such as amplitude or peaks. In addition, there is a relationship between the activity intensity and biometric response, which can be considered together with acceleration data to improve the accuracy of activity detection. The proposed algorithm is designed to work with minimum computational cost, being ready to run in a mobile device as part of a context-aware application. In order to enable different user scenarios, the algorithm offers best-effort activity estimation: its quality of estimation depends on the position and number of the available inertial sensors, and also on the presence of biometric information.

The CDG, UDG, and MEL methods for automatic compile-time parallelization of logic programs for independent and-parallelism

There has been significant interest in parallel execution models for logic programs which exploit Independent And-Parallelism (IAP). In these models, it is necessary to determine which goals are independent and therefore eligible for parallel execution and which goals have to wait for which others during execution. Although this can be done at run-time, it can imply a very heavy overhead. In this paper, we present three algorithms for automatic compiletime parallelization of logic programs using IAP. This is done by converting a clause into a graph-based computational form and then transforming this graph into linear expressions based on &-Prolog, a language for IAP. We also present an algorithm which, given a clause, determines if there is any loss of parallelism due to linearization, for the case in which only unconditional parallelism is desired. Finally, the performance of these annotation algorithms is discussed for some benchmark programs.

Complete and efficient methods for supporting side effects in independent/restricted and-parallelism

It has been shown that it is possible to exploit Independent/Restricted And-parallelism in logic programs while retaining the conventional "don't know" semantics of such programs. In particular, it is possible to parallelize pure Prolog programs while maintaining the semantics of the language. However, when builtin side-effects (such as write or assert) appear in the program, if an identical observable behaviour to that of sequential Prolog implementations is to be preserved, such side-effects have to be properly sequenced. Previously proposed solutions to this problem are either incomplete (lacking, for example, backtracking semantics) or they force sequentialization of significant portions of the execution graph which could otherwise run in parallel. In this paper a series of side-effect synchronization methods are proposed which incur lower overhead and allow more parallelism than those previously proposed. Most importantly, and unlike previous proposals, they have well-defined backward execution behaviour and require only a small modification to a given (And-parallel) Prolog implementation.

Phonotactic language recognition using i-vectors and phoneme posteriogram counts

This paper describes a novel approach to phonotactic LID, where instead of using soft-counts based on phoneme lattices, we use posteriogram to obtain n-gram counts. The high-dimensional vectors of counts are reduced to low-dimensional units for which we adapted the commonly used term i-vectors. The reduction is based on multinomial subspace modeling and is designed to work in the total-variability space. The proposed technique was tested on the NIST 2009 LRE set with better results to a system based on using soft-counts (Cavg on 30s: 3.15% vs 3.43%), and with very good results when fused with an acoustic i-vector LID system (Cavg on 30s acoustic 2.4% vs 1.25%). The proposed technique is also compared with another low dimensional projection system based on PCA. In comparison with the original soft-counts, the proposed technique provides better results, reduces the problems due to sparse counts, and avoids the process of using pruning techniques when creating the lattices.

Concrete constitutive model, calibration and applications

A methodology has been developed for characterising the mechanical behaviour of concrete, based on the damaged plasticity model, enriched with a user subroutine (V)USDFLD in order to capture better the ductility of the material under moderate confining pressures. The model has been applied in the context of the international benchmark IRIS_2012, organised by the OECD/NEA/CSNI Nuclear Energy Agency, dealing with impacts of rigid and deformable missiles against reinforced concrete targets. A slightly modified version of the concrete damaged plasticity model was used to represent the concrete. The simulation results matched very well the observations made during the actual tests. Particularly successful predictions involved the energy spent by the rigid missile in perforating the target, the crushed length of the deformable missile, the crushed and cracked areas of the concrete target, and the values of the strains recorded at a number of locations in the concrete slab.