Levels Of Available Data Research Articles

Prevalence of elephantiasis, an overlooked disease in Southern Africa: a comprehensive review.

Elephantiasis, also known as lymphatic filariasis (LF), is a debilitating condition characterized by the thickening of the skin and muscles, primarily affecting the limbs, genitalia, and female breasts. Lymphatic filariasis is a major global health concern, affecting approximately 120 million people worldwide and having a significant impact on people's quality of life, mobility, and socio-economic status. Although LF is endemic in many parts of the world, including Africa, it is a neglected issue in Southern Africa, with little information available. According to the World Health Organisation, approximately 882.5 million people in 44 countries worldwide are at risk of contracting LF, making it the second most common vector-borne disease after malaria. The primary goal of this review was to assess the prevalence of elephantiasis in the Southern African Development Community (SADC) region. Lymphatic filariasis is endemic in four of the sixteen SADC countries, three countries have administered MDA to the population that required it and they are now under post-intervention surveillance, while LF is no longer a public health problem in Malawi. Global efforts to eliminate LF have been hampered by the non-availability of MDA in some SADC countries such as Angola, Mozambique, Zambia, and Zimbabwe. Despite the implementation of mass drug administration programs, a review of the literature reveals gaps in knowledge about LF prevalence cases in SADC countries. Each country faces unique challenges and successes in combating LF due to varying levels of available data and healthcare infrastructure. Some SADC countries continue to bear the burden of LF-related diseases, necessitating ongoing disease prevention and elimination efforts. This review emphasizes the importance of ongoing research, data collection, and novel policies to combat the spread of elephantiasis disease in the SADC region and beyond.

Method for estimating the probability of geological success: A case study of the HRA-E prospect, Block 106, northern Song Hong basin

Petroleum exploration and drilling represent fields fraught with inherent uncertainties, consequently, geological assessment is significantly important for precisely selecting prospects and well locations. The geological evaluation of prospective formations predominantly relies on 5 elements of the petroleum system including source, reservoir, seal, trap, and migration.This article introduces globally applied geological assessment methods, and proposes an applicable methodology for exploration targets across regions with varying levels of available data. Applying this method of evaluating risk criteria for pre-Cenozoic carbonate objects of HRA-E prospect in Block 106 shows that the evaluation results align with the actual probability of success in drilling exploration activities in the region and could be extended to other projects within the Petrovietnam Exploration Production Corporation (PVEP).

Ready or not, here it comes: Assessing the gaps in community plans for renewable energy transitions within the United States

At global and national scales, renewable energy transitions aimed at climate change mitigation are slower than anticipated. In response, regional and localized entities have taken matters into their own hands to promote expedited progress. Over 200 communities in the United States (states, counties, cities, and townships) have made public pledges to achieve a 100 % renewable energy (or electricity) transition. However, there is still uncertainty in how the operational, technological, managerial, and infrastructural transitions will occur – and despite growing support for energy transitions, there are still significant gaps in the plans set forth. Within this study, the available information from 186 entities that have made a pledge towards 100 % renewable energy was synthesized to illustrate where there are gaps in energy transition plans. At the highest level of available data, only 40 % of communities had a public facing action plan for their transition goals. This metric alone suggests (alongside additional results) that there are significant shortcomings in the existing plans for energy transitions even at the community scale. This calls for reconsidering communication strategies and broadening participation when these transition plans are being discussed, as well as a reassessment of what policy tools are in place to encourage and support these transitions.

QoS-Based Contract Design for Profit Maximization in IoT-Enabled Data Markets

The massive deployment of Internet of Things (IoT) devices, including sensors and actuators, is ushering in smart and connected communities of the future. The massive deployment of Internet of Things (IoT) devices, including sensors and actuators, is ushering in smart and connected communities of the future. The availability of real-time and high-quality sensor data is crucial for various IoT applications, particularly in healthcare, energy, transportation, etc. However, data collection may have to be outsourced to external service providers (SPs) due to cost considerations or lack of specialized equipment. Hence, the data market plays a critical role in such scenarios where SPs have different quality levels of available data, and IoT users have different application-specific data needs. The pairing between data available to the SP and users in the data market requires an effective mechanism design that considers the SPs’ profitability and the quality-of-service (QoS) needs of the users. We develop a generic framework to analyze and enable such interactions efficiently, leveraging tools from contract theory and mechanism design theory. It can enable and empower emerging data sharing paradigms such as Sensing-as-a-Service (SaaS). The contract design creates a pricing structure for on-demand sensing data for IoT users. By considering a continuum of user types, we capture a diverse range of application requirements and propose optimal pricing and allocation rules that ensure QoS provisioning and maximum profitability for the SP. Furthermore, we provide analytical solutions for fixed distributions of user types to analyze the developed approach. For comparison, we consider the benchmark case assuming complete information of the user types and obtain optimal contract solutions. Finally, a case study based on the example of virtual reality application delivered using unmanned aerial vehicles (UAVs) is presented to demonstrate the efficacy of the proposed contract design framework.

Dealing With Data Uncertainty for Transformer Insulation System Health Index

Health index has been widely accepted as a powerful tool for monitoring the condition of power transformer insulation system based on various diagnostic parameters. While this approach has been extensively discussed in the literature, not much attention was given to provide effective solutions to the uncertainty in the used data. According to CIGRE 761, data quality issues may arise due to measurement accuracy as well as incompleteness and unavailability of the required data. Therefore, this article presents the implementation and evaluation of a certainty level model for transformer insulation system health index to deal with data uncertainty. The impact of data unavailability on the health index results is also investigated. Certainty level of the health index is determined by the criticality level of available data, and is reported along with the health index result. A method to handle unavailable data by predicting the oil interfacial tension (IFT) using Random Forest approach is also presented. The proposed certainty level model is designed to accommodate the predicted value of missed data into the health index model while considering its prediction accuracy. The robustness of the developed model is validated through its application in assessing the health condition of six in-service power transformers. The results indicate that by including the proposed certainty level and the prediction approach to eliminate the issue of uncertain and missed diagnostic data, an asset management decision can be taken on operating power transformer fleets with high level of confidence.

DETERMINING FACTORS OF TEACHERS’ SELF-EFFICACY IN COUNTRIES OF THE EUROPEAN UNION. RESULTS FROM TALIS 2013

Over the last few years, the effect that teachers’ beliefs have on the results achieved by their students has been widely studied. Educational research has shown that the self-efficacy beliefs of teachers in their work influence their professional behavior and are associated with students’ achievement and motivation. The main aim of this work is to study the personal and contextual factors determining the level of self-efficacy perceived by teachers in countries of the European Union which participated in TALIS 2013. Specifically, it attempts to answer the following questions: What are the main determinants of teachers’ self-efficacy beliefs? Are these factors individual or contextual? Do these determinants vary from country to country? Taking into account the multistructural level of available data (teachers —Level 1— are nested within schools —Level 2— in each country), data analysis has been carried out by means of multilevel structural equation modeling. More specifically, a multigroup multilevel model has been designed to study the effect of teachers’ traits (Level 1 predictors) and school traits (Level 2 predictors) on the perceived level of self-efficacy in different countries. The results show that variables relating to the teachers as professionals (cooperation with their colleagues, encouraging self-evaluation by the students, teachers’ perception of satisfactory class discipline, a need for professional development in the contents of the subject taught and in teaching skills, and having a constructivist teaching approach) are the ones most closely related to their self-efficacy beliefs. These are more important than factors associated with the institutional setting in which they work (ownership, ratio, or shortage of resources), or strictly personal traits (age, gender, or work situation).

Conducting Retrospective Analyses of Building Energy Models with Various Levels of Available Data

AbstractBuilding owners and design teams rely greatly on building energy models to identify effective strategies for maximizing building energy performance. However, past studies of building energy-model performance, particularly among Leadership in Energy and Environmental Design (LEED)-certified buildings, have shown that models can vary significantly at the individual building level. Conducting retrospective analyses of building energy models can provide more insight regarding empirical variation and models’ sources of error than past studies that reported the observed difference between predicted and actual annual energy performances. This paper describes a method for conducting retrospective analyses on building-energy models, and then applies the method to three LEED-certified dormitory buildings that are owned and operated by the U.S. Department of Defense. All three buildings contained varying levels of actual building-energy data, which served to illustrate the extent to which model error may be ...

Estimation of the compression behaviour of reconstituted clays

The void index is a relative quantity measuring the position of the current void ratio of a clay against the void ratios of the clay at two specific vertical effective stresses (i.e., σv′=100kPa and σv′=1000kPa). Based on this concept, a simple systematic tool is proposed for estimating the compression behaviour of reconstituted clays over a wide range of stresses and water contents. Following the practice of geotechnical engineering computation, the compression behaviour of clays is idealised as linear segments in the Iv~lnp′ (or the void index and the mean effective stress) space. Considering the variation in the available data, there are three related but independent models for describing the compression behaviour of reconstituted clays. The accuracy of estimation increases with the level of available data. The proposed estimation is used to simulate the behaviour of a variety of reconstituted clays over a wide range of stresses and water contents. With different levels of available data, the estimation is evaluated on the basis of these simulations. The proposed estimation can take maximum use of available data and provide a simple yet practical tool for calculating the compression behaviour of reconstituted clays and a basic parameter for geotechnical engineering computations, the compression index. An empirical equation for the initial compression index is also suggested and verified.

하구 환경관리를 위한 관리구역 경계 설정방안

실질적인 하구환경의 관리를 위해서는 관리구역, 즉 하구역이 먼저 정의되어야 한다. 그러나 하구역의 경계를 설정할 수 있는 과학적 자료의 부족으로 인해 아직까지 체계적인 경계설정 방법이 제시되지 못하고 있다. 본 연구는 하구의 물리화학적 특성 등의 과학적 자료와 더불어 지리 지형적 특성 및 이용개발 특성 등을 종합적으로 고려하여 체계적으로 하구역 경계를 설정하는 방법을 제안하였다. 하구를 하구순환의 유지여부에 따라 열린 하구와 닫힌 하구로 구분하고, 각 유형에 속한 개별 하구에 대해 물리화학, 지리지형학 및 이용개발 특성을 고려하여 하구수역의 경계를 설정한 후에 하구수역에 영향을 미치는 하구육역의 경계를 설정하는 순차적인 방법이다. 이 방법에 따라 국내 274개 하구역의 경계를 시범적으로 설정해본 결과 각 하구별로 가용한 자료의 수준과 지역 특성의 차이를 합리적으로 고려한 하구역 경계 설정이 가능한 것으로 나타났다. Definition of estuary and its administrative boundaries is needed for the practical management of estuarine environment. However, the majority of Korean estuaries are lack of scientific data required for defining the administrative boundaries. For this reason, a systematic way to set the boundaries has not been developed so far. This study proposed adaptive and comprehensive criteria in defining the boundary of an estuary based on the available data which includes physiochemical, geographical and topographical characteristics and regional data such as land uses and socio-economic conditions. An estuary boundary is defined with a sequential manner. First of all, according to the estuarine circulation pattern, 463 estuaries in Korea were classified into open estuaries and closed estuaries. Then an individual belonging to each type of estuary is defined an water zone boundary considering the physiochemical, geographical and topographical characteristics and land uses. Finally, a land zone boundary is set along the catchment. According to the proposed criteria, we have delineated 274 estuarine management zones in Korea on a trial basis and found that it was possible to set a boundary reasonably considering the difference of level of available data and regional characteristics in each estuary.

Development of screening tools for the interpretation of chemical biomonitoring data.

Evaluation of a larger number of chemicals in commerce from the perspective of potential human health risk has become a focus of attention in North America and Europe. Screening-level chemical risk assessment evaluations consider both exposure and hazard. Exposures are increasingly being evaluated through biomonitoring studies in humans. Interpreting human biomonitoring results requires comparison to toxicity guidance values. However, conventional chemical-specific risk assessments result in identification of toxicity-based exposure guidance values such as tolerable daily intakes (TDIs) as applied doses that cannot directly be used to evaluate exposure information provided by biomonitoring data in a health risk context. This paper describes a variety of approaches for development of screening-level exposure guidance values with translation from an external dose to a biomarker concentration framework for interpreting biomonitoring data in a risk context. Applications of tools and concepts including biomonitoring equivalents (BEs), the threshold of toxicologic concern (TTC), and generic toxicokinetic and physiologically based toxicokinetic models are described. These approaches employ varying levels of existing chemical-specific data, chemical class-specific assessments, and generic modeling tools in response to varying levels of available data in order to allow assessment and prioritization of chemical exposures for refined assessment in a risk management context.

Novel Approach in Pipe Condition Scoring

A major challenge in sewer and water pipe infrastructure management is determining structural condition scores for pipe assets. The methodology used to determine the condition of pipes should be relevant, repeatable, and validated. Additionally, to be appropriate for use in risk-analysis models, the scale selected to represent the structural condition should be linear. The methodology developed in this paper enables previously developed pipe statistical failure models to be translated into a mean time to failure (MTF) for individual pipes. By using the economic concept of discounting, the MTF is then used to score the structural condition of the pipe, providing an appropriate structural condition score for use in risk-based asset management models. This methodology for determining the structural condition score has several advantages over previously developed models: the results can be easily interpreted and validated, and the resulting scale is linear. Additionally, the system can be implemented for pipes with differing levels of available data, such as for pipes with and without inspection results.

Estimation of Macropore Properties for No-till Soils

Macropores contribute to rapid movement of water and solutes through the soil. Determining the size and distribution of macropore requires laborious field and/or laboratory procedures. The objective of this study was to develop methods for estimating macropore size and distribution based on more easily obtained data such as soil texture, one set of pore size, and count and/or macropore saturated hydraulic conductivity. Algorithms based on fractal geometry were developed to estimate the soil macropore properties of macropore sizes/counts, areal porosity, and/or saturated hydraulic conductivity. A database representing five soil textures under a no-till farming practice was used to develop empirical equations to calculate macropore size/count, areal porosity, and macropore conductivity based on three levels of available data. The three levels of input data are soil texture and (1) an arbitrary size (Rx) and pore count above that size (Nx); (2) a measured macropore saturated hydraulic conductivity (Kmacro); or (3) an estimated largest macropore radius (R1). The form of all regression equations were shown to be consistent with equations from fractal geometry. The developed equations were tested with independent, published macropore data and their reported variances. The verifications indicated that satisfactory estimates of macropore size/counts, areal porosity, and saturated conductivity can be made from more readily available macropore data.

Maternal and child health: use of health status indicators in coordinating and targeting federal programs.

The United States has achieved dramatic improvements in overall maternal and child health status, yet faces disturbingly wide variations in the health status of many population subgroups. The Surgeon General in 1980 published specific quantitative objectives to stimulate further improvements in the health of the American people by 1990. A critical step in meeting relevant objectives is the more effective use at national, state, and local levels of available data, particularly infant, perinatal, neonatal, and maternal mortality rates and the incidence of low weight births. This paper reviews variations in infant mortality rates and five current federal "categorical" programs that aim to improve maternal and child health: Supplemental Feeding Program for Women, Infants and Children; Head Start; Maternal and Child Health; Family Planning; and Community Health Centers. Several examples are cited of effective use of data in the coordination and targeting of resources from these large public programs. Recommendations are made for enhancement of federal maternal and child health programs within current funding levels. These recommendations will be all the more relevant if the Congress enacts block grants to the states with lower total funding.