Influencing effect of heat-treatment on radon emanation and exhalation characteristic of red mud

The reuse of industrial by-products is important for members of numerous industrial sectors. However, though the benefits of reuse are evident from an economical point of view, some compounds in these materials can have a negative effect on users' health.In this study, the radon emanation and exhalation features of red mud were surveyed using heat-treatment (100-1200 °C). As a result of the 1200°C-treated samples, massic radon exhalation capacity reduced from 75 ± 10 mBq kg^-1 h^-1 to 7 ± 4 mBq kg^-1 h^-1, approximately 10% of the initial exhalation rate.To find an explanation for internal structural changes, the porosity features of the heat-treated samples were also investigated. It was found that the cumulative pore volume reduced significantly in less than 100 nm, which can explain the reduced massic exhalation capacity in the high temperature treated range mentioned above.SEM snapshots were taken of the surfaces of the samples as visual evidence for superficial morphological changes. It was found that the surface of the high temperature treated samples had changed, proving the decrement of open pores on the surface.

Electron acoustic soliton energy of the Kadomtsev-Petviashvili equation in the Earth’s magnetotail region at critical ion density

The nonlinear properties of small amplitude electron-acoustic solitary waves (EAWs) in a homogeneous system of unmagnetized collisionless plasma consisted of a cold electron fluid and isothermal ions with two different temperatures obeying Boltzmann type distributions have been investigated. A reductive perturbation method was employed to obtain the Kadomstev-Petviashvili (KP) equation. At the critical ion density, the KP equation is not appropriate for describing the system. Hence, a new set of stretched coordinates
is considered to derive the modified KP equation. Moreover, the solitary solution, soliton energy and the associated electric field at the critical ion density were computed. The present investigation can be of relevance to the electrostatic solitary structures observed in various space plasma environments, such as Earth’s magnetotail region.

Symmetries and exact solutions of KP equation with an arbitrary nonlinear term

The generalized KP (GKP) equations with an arbitrary nonlinear term model and characterize many nonlinear physical phenomena. The symmetries of GKP equation with an arbitrary nonlinear term are obtained. The condition that must satisfy for existence the symmetries group of GKP is derived and also the obtained symmetries are classified according to different forms of the nonlinear term. The resulting similarity reductions are studied by performing the bifurcation and the phase portrait of GKP and also the corresponding solitary wave solutions of GKP
equation are constructed.

A Simultaneous Equation Approach to Estimating HIV Prevalence with Non-Ignorable Missing Responses

Estimates of HIV prevalence are important for policy in order to establish the health status of a country's population and to evaluate the effectiveness of population-based interventions and campaigns. However, participation rates in testing for surveillance conducted as part of household surveys, on which many of these estimates are based, can be low. HIV positive individuals may be less likely to participate because they fear disclosure, in which case estimates obtained using conventional approaches to deal with missing data, such as imputation-based methods, will be biased. We develop a Heckman-type simultaneous equation approach which accounts for non-ignorable selection, but unlike previous implementations, allows for spatial dependence and does not impose a homogeneous selection process on all respondents. In addition, our framework addresses the issue of separation, where for instance some factors are severely unbalanced and highly predictive of the response, which would ordinarily prevent model convergence. Estimation is carried out within a penalized likelihood framework where smoothing is achieved using a parametrization of the smoothing criterion which makes estimation more stable and efficient. We provide the software for straightforward implementation of the proposed approach, and apply our methodology to estimating national and sub-national HIV prevalence in Swaziland, Zimbabwe and Zambia.

Meningeal alveolar soft part sarcoma confirmed by characteristic ASPCR1-TFE3 fusion

Sarcoma metastatic to the brain is uncommon and rarely occurs as the initial manifestation of tumor. Alveolar soft part sarcoma (ASPS) is a rare but well-studied subtype of sarcoma. A 39-year-old man presented with seizures due to a left temporal meningeal-enhancing lesion with striking brain edema on MRI. The patient underwent neurosurgical resection for suspected meningioma. Histology showed large tumor cells clustering and forming small nests, in places with pseudoalveolar pattern. Diastase-resistant periodic acid-Schiff revealed very rare granular and rod-like cytoplasmic inclusions. Immunohistochemistry showed convincing positivity only with vimentin and smooth muscle actin. The histological features were strongly suggestive of ASPS. At the molecular level RT-PCR and sequencing analysis demonstrated ASPCR1-TFE3 fusion confirming the histological diagnosis of ASPS. There was no evidence of primary extracranial tumor by physical examination and on chest and abdominal CT scan 11 months after presentation. ASPS typically arise from the soft tissues of the extremities and develop multiple metastatic deposits usually with a long clinical course. This case may represent primary meningeal ASPS although metastatic deposit from an undiscovered primary site cannot be entirely excluded.

Automated Equation Formulation for Causal Loop Diagrams

The annotation of Business Dynamics models with parameters and equations, to simulate the system under study and further evaluate its simulation output, typically involves a lot of manual work. In this paper we present an approach for automated equation formulation of a given Causal Loop Diagram (CLD) and a set of associated time series with the help of neural network evolution (NEvo). NEvo enables the automated retrieval of surrogate equations for each quantity in the given CLD, hence it produces a fully annotated CLD that can be used for later simulations to predict future KPI development. In the end of the paper, we provide a detailed evaluation of NEvo on a business use-case to demonstrate its single step prediction capabilities.