MAXIPOL: a balloon-borne experiment for measuring the polarization anisotropy of the cosmic microwave background radiation

We discuss MAXIPOL, a bolometric balloon-borne experiment designed to measure the E-mode polarization anisotropy of the cosmic microwave background radiation (CMB) on angular scales of 10^′ to 2°. MAXIPOL is the first CMB experiment to collect data with a polarimeter that utilizes a rotating half-wave plate and fixed wire-grid polarizer. We present the instrument design, elaborate on the polarimeter strategy and show the instrument performance during flight with some time domain data. Our primary dataset was collected during a 26 h turnaround flight that was launched from the National Scientific Ballooning Facility in Ft. Sumner, New Mexico in May 2003. During this flight five regions of the sky were mapped. Data analysis is in progress.     

Study on the kinetics of iron oxide leaching by oxalic acid

The presence of iron oxides in clay or silica raw materials is detrimental to the manufacturing of high quality ceramics. Although iron has been traditionally removed by physical mineral processing, acid washing has been tested as it is more effective, especially for extremely low iron (of less than 0.1% w/w). However, inorganic acids such as sulphuric or hydrochloric acids easily contaminate the clay products with SO₄²⁻ and Cl⁻, and therefore should be avoided as much as possible. On the other hand, if oxalic acid is used, any acid left behind will be destroyed during the firing of the ceramic products. The characteristics of dissolution of iron oxides were therefore investigated in this study.The dissolution of iron oxides in oxalic acid was found to be very slow at temperatures within the range 25–60 °C, but its rate increases rapidly above 90 °C. The dissolution rate also increases with increasing oxalate concentration at the constant pH values set within the optimum range of pH2.5–3.0. At this optimum pH, the dissolution of fine pure hematite (Fe₂O₃) (105–140 μm) follows a diffusion-controlled shrinking core model. The rate expression expressed as 1 − (2 / 3)x − (1 − x)^2 / 3 where x is a fraction of iron dissolution was found to be proportional to [oxalate]^1.5.The addition of magnetite to the leach liquor at 10% w/w hematite was found to enhance the dissolution rate dramatically. Such addition of magnetite allows coarser hematite in the range 0.5–1.4 mm to be leached at a reasonable rate.     

Drought in Bulgaria and atmospheric synoptic conditions over Europe

Drought in Bulgaria is analyzed from the multiple viewpoints of statistical occurrence, spatial patterns, and synoptic conditions. A new index of drought, the SD (spatial-dryness) index, characterizes drought by both intensity and spatial extent. The occurrence of the SD index is analyzed using global gridded data sets. Examination of transitional probabilities of multiple months and years with drought occurrence suggests persistence is sufficiently frequent to be important for climate-related environmental planning. Finally, it is shown that specific seasonal synoptic patterns are associated with wet and dry conditions in Bulgaria. This revised version was published online in July 2006 with corrections to the Cover Date.     

Flood-prone area mapping using machine learning techniques: a case study of Quang Binh province,Vietnam

Natural Hazards - Vietnam’s central coastal region is the most vulnerable and always at flood risk, severely affecting people’s livelihoods and socio-economic development. In...     

Predicting rock size distribution in mine blasting using various novel soft computing models based on meta-heuristics and machine learning algorithms

Blasting is well-known as an effective method for fragmenting or moving rock in open-pit mines. To evaluate the quality of blasting, the size of rock distribution is used as a critical criterion in blasting operations. A high percentage of oversized rocks generated by blasting operations can lead to economic and environmental damage. Therefore, this study proposed four novel intelligent models to predict the size of rock distribution in mine blasting in order to optimize blasting parameters, as well as the efficiency of blasting operation in open mines. Accordingly, a nature-inspired algorithm (i.e., firefly algorithm – FFA) and different machine learning algorithms (i.e., gradient boosting machine (GBM), support vector machine (SVM), Gaussian process (GP), and artificial neural network (ANN)) were combined for this aim, abbreviated as FFA-GBM, FFA-SVM, FFA-GP, and FFA-ANN, respectively. Subsequently, predicted results from the abovementioned models were compared with each other using three statistical indicators (e.g., mean absolute error, root-mean-squared error, and correlation coefficient) and color intensity method. For developing and simulating the size of rock in blasting operations, 136 blasting events with their images were collected and analyzed by the Split-Desktop software. In which, 111 events were randomly selected for the development and optimization of the models. Subsequently, the remaining 25 blasting events were applied to confirm the accuracy of the proposed models. Herein, blast design parameters were regarded as input variables to predict the size of rock in blasting operations. Finally, the obtained results revealed that the FFA is a robust optimization algorithm for estimating rock fragmentation in bench blasting. Among the models developed in this study, FFA-GBM provided the highest accuracy in predicting the size of fragmented rocks. The other techniques (i.e., FFA-SVM, FFA-GP, and FFA-ANN) yielded lower computational stability and efficiency. Hence, the FFA-GBM model can be used as a powerful and precise soft computing tool that can be applied to practical engineering cases aiming to improve the quality of blasting and rock fragmentation.     

Prediction of Rock Size Distribution in Mine Bench Blasting Using a Novel Ant Colony Optimization-Based Boosted Regression Tree Technique

Natural Resources Research - In this paper, we used artificial intelligence (AI) techniques to investigate the relation between the rock size distribution (RSD) and blasting parameters for rock...     

A study of coral reef resilience and implications of adaptive management and rehabilitation in Khanh Hoa Province, Vietnam

The Province of Khanh Hoa, Vietnam, is located in the western South China Sea and boasts a shoreline of 385 km and many islands. Previous studies have indicated the extreme diversity and abundance of coral reefs in its waters as compared with other coastal provinces of Vietnam. A study on the resilience of coral reefs against increased surface water temperature and anthropogenic impact is conducted at 19 reef sites in 2015. At each site, a series of parameters (e.g., coral covers, genus diversity, and coral recruitment, substratum heterogeneity, depth, water exchange level, and sediment deposit and water temperature) are measured quantitatively or semi-quantitatively. The measured data are rated based on the relationship between the parameter values and coral susceptibility; the consideration that reef health reflects the biological capability to adapt to environmental changes and the recruitment potential if bleached; and positive or negative influences of physical factors in the mitigation of thermal stress and protecting corals from bleaching. A cumulative analysis enables researchers to divide the studied reefs into four categories based on varying levels of reef health to support resilience, recovery, and vulnerability in the case of increased water temperature. Relevant management interventions for each category and other supporting activities are suggested to enhance management effectiveness and to plan the rehabilitation of coral reefs for biodiversity conservation and touristic development, taking into account the involvement of related stakeholders.     

Multifractal behaviour of long‐term karstic discharge fluctuations

Karstic watersheds are highly complex hydrogeological systems that are characterized by a multiscale behaviour corresponding to the different pathways of water in these systems. The main issue of karstic spring discharge fluctuations consists in the presence and the identification of characteristic time scales in the discharge time series. To identify and characterize these dynamics, we acquired, for many years at the outlet of two karstic watersheds in South of France, discharge data at 3‐mn, 30‐mn and daily sampling rate. These hydrological records constitute to our knowledge the longest uninterrupted discharge time series available at these sampling rates. The analysis of the hydrological records at different levels of detail leads to a natural scale analysis of these time series in a multifractal framework. From a universal class of multifractal models based on cascade multiplicative processes, the time series first highlights two cut‐off scales around 1 and 16 h that correspond to distinct responses of the aquifer drainage system. Then we provide estimates of the multifractal parameters α and C₁ and the moment of divergence q_D corresponding to the behaviour of karstic systems. These results constitute the first estimates of the multifractal characteristics of karstic spingflows based on 10 years of high‐resolution discharge time series and should lead to several improvements in rainfall‐karstic springflow simulation models. Copyright © 2012 John Wiley & Sons, Ltd.