6 research outputs found
Effective conductivity of an anisotropic heterogeneous medium of random conductivity distribution
No full text"\"The paper deals with the effective conductivity tensor K(ef) of anisotropic random media subject to mean uniform flux. The hydraulic conductivity K field is modeled as a collection of spheroidal disjoint inclusions of different, isotropic and independent Y = ln K; the latter is a random variable with given distribution of variance sigma(2)(Y). Inclusions are embedded in homogeneous background of anisotropic conductivity K(0). The K field is anisotropic, characterized by the anisotropy ratio f, ratio of the vertical and horizontal integral scales of K. We derive K(ef) by accurate numerical simulations; the numerical model for anisotropic media is presented here for the first time, and it generalizes a previously developed model for isotropic formations [I. Jankovic, A. Fiori, and G. Dagan, Multiscale Model. Simul., 1 (2003), pp. 40-56]. The numerical model is capable of solving complex three-dimensional flow problems with high accuracy for any configuration of the spheroidal inclusions and arbitrary K distribution. The numerically derived K(ef) for a normal Y is compared with its prediction by (i) the self-consistent solution K(sc), (ii) the first-order approximation in sigma(2)(Y), and (iii) the exponential conjecture [L. J. Gelhar and C. L. Axness Water. Resour. Res., 19 (1983), pp. 161-180]. It is found that the self-consistent solution K(sc) is very accurate for a broad range of the values of the parameters sigma(2)(Y), f and for the densest inclusions packing. In contrast, the first-order solution strongly deviates from K(ef) for large sigma(2)(Y), as expected, and the exponential conjecture is generally unable to correctly represent the effective conductivity. The numerical solution for the potential is expressed as an infinite series of spheroidal harmonics, attached to the interior and exterior of each inclusion, which accounts for the nonlinear interaction between neighboring inclusions.\"
Identification of heterogeneous aquifer transmissivity using an AE-based method RID A-2321-2010
No full textDetermination of hydraulic head, H, as a function of spatial coordinates and time, in ground water flow is the basis for aquifer management and for prediction of contaminant transport. Several computer codes are available for this purpose. Spatial distribution of the transmissivity, T( x, y), is a required input to these codes. In most aquifers, T varies in an erratic manner, and it can be characterized statistically in terms of a few moments: the expected value, the variance, and the variogram. Knowledge of these moments, combined with a few measurements, permits one to estimate T at any point using geostatistical methods. In a review of transmissivity data from 19 unconsolidated aquifers, Hoeksema and Kitanidis ( 1985) identified two types of the logtransmissivity Y = In( T) variations: correlated variations with variance sigma(Yc)(2) and correlation scale, I-Y, on the order of kilometers, and uncorrelated variations with variance sigma(Yn)(2). Direct identification of the logtransmissivity variogram, Gamma(Y), from measurements is difficult because T data are generally scarce. However, many head measurements are commonly available. The aim of the paper is to introduce a methodology to identify the transmissivity variogram parameters (sigma(Yc)(2), I-Y, and sigma(Yn])(2)) using head data in formations characterized by large logtransmissivity variance. The identification methodology uses a combination of precise numerical simulations ( carried out using analytic element method) and a theoretical model. The main objective is to demonstrate the application of the methodology to a regional ground water flow in Eagle Valley basin in west- central Nevada for which abundant transmissivity and head measurements are available
Statistical analysis of head and transmissivity in natural aquifers: application to structure identification and transport prediction
No full textThe First Detection of X-Ray Polarization in a Newly Discovered Galactic Transient Swift J151857.0-572147
No full textWe study the spectropolarimetric properties of a newly discovered black hole (BH) X-ray binary Swift J151857.0-572147 jointly using Imaging X-ray Polarimetry Explorer (IXPE) and NuSTAR observations during 2024 March. The analysis of IXPE data reports the first detection of X-ray with a polarization degree (PD) of 1.34 ± 0.27 and a polarization angle (PA) of −13.°69 ± 5.°85 using a model-independent approach, while the model-dependent analysis gives a PD of 1.18 ± 0.23 and a PA of −14.°01 ± 5.°80. The joint spectral analysis of the broadband data and NuSTAR analysis in isolation constrain the mass of the central BH between ∼9.2 ± 1.6 and 10.1 ± 1.7 M _⊙ and a moderate spin parameter of ∼0.6 ± 0.1–0.7 ± 0.2 with a disk inclination of ∼35° ± 7°–46° ± 15°. The power-law photon index and cutoff energy are 2.19 ± 0.03–2.47 ± 0.06 and ∼36 ± 4–78 ± 10 keV, suggesting a transition to the soft spectral state. Additionally, a relatively lower corona size of 6 ± 1–9 ± 2 r _S , a low mass outflow rate ( ), and the best-fitted halo accretion is less compared to the disk accretion rate further confirm the same state. The low PD detected in the soft state can be due to repeated scattering inside the dense corona, and the dominant emission from the disk agrees with the low spin and low disk inclination. The hydrogen column density obtained from the fit is relatively high at ∼4–5 × 10 ^22 cm ^−2
Cognitive profiles of vascular and neurodegenerative MCI
No full textThe objective of the thesis was to investigate the cognitive profiles of different types of mild cognitive impairment (MCI) and follow their course over time. Would it be possible to differentiate between “benign” and “malign” forms of MCI, and identify different dementia disorders in their prodromal stages by means of cognitive profiles? In study I consecutive MCI subjects (N=112) were assessed with a neuropsyhological test battery of 21 tests. When compared to healthy controls (N=35) MCI subjects had impairments in all cognitive domains (speed/attention, memory and learning, visuospatial functions, language and executive functions), which contradicted the prevailing view of MCI typically being memory impairment, ”amnestic MCI”. In study II the subjects were grouped by cerebrovascular disease. Subjects with significant vascular disease (N=60) performed overall worse on the neuropsychological test battery than those without vascular disease (N=60). The most clear-cut differences were seen on speed/attention and executive tests, and the conclusion was that there were similarities in the cognitive profiles of MCI with vascular disease and vascular dementia. In study III MCI subjects without vascular disease were grouped by concentrations of the Alzheimer-typical biomarkers total-tau (T-tau) and beta-amyloid (Aß). Subjects with Alzheimer-typical concentrations of one or the other or both biomakers in cerebrospinal fluid (N=73) performed worse on episodic memory and speed/attention tests than those with normal concentrations (N=73). When subjects were grouped into those with only high T-tau, only low Aß and both high T-tau and low Aß, those with both high T-tau and low Aß tended to perform slightly worse, while the other two groups performed quite similarly. In study IV 175 subjects were followed up after two years. Forty-four converted to dementia, all with impairment in several cognitive domains at baseline, and all but two had either vascular disease or Alzheimer-typical biomarkers. Single domain MCI – regardless of vascular disease and biomarkers – had a benign prognosis over two years. The combination of multiple domain amnestic MCI and vascular disease was the best predictor of mixed and vascular dementia, while multiple domain amnestic MCI and biomarkers was the strongest predictor of Alzheimer’s disease. MCI is a heterogeneous condition – the original purely amnestic MCI was very rare – w ith several aetiologies. The combination of cognitive profiles and aetiologies has the potential of making a crucial contribution in diagnosing dementia disorders at their earliest manifestations
Investigating the psychometric properties of a South African adaptation of the Boston Naming Test : evidence for diagnostic validity from a memory clinic population
No full textIncludes abstract.The Boston Naming Test (BNT) is a popular confrontation naming test that is frequently used in the detection of naming deficits in Alzheimer's disease (AD). However, the test may not be appropriate when used outside of North America due to the influence of varying word frequency and familiarity between different cultures and languages. This study investigated the diagnostic validity of a South African 15-item adaption of the BNT (the BNT-SA-SF) in a Cape Town memory clinic population of patients with dementia and healthy, community-dwelling control participants. Between-groups comparisons, receiver operating characteristic (ROC) analyses, and other diagnostic efficiency statistics were used to assess the test's discriminative capacity between patients with AD (n = 46), patients with other types of dementia (n = 23), and controls (n = 51), matched on key demographic variables. The AD group performed worse than patients with other types of dementia and controls on the BNT-SA-SF, and patients with other types of dementia scored more poorly than controls. The test showed the most significant discriminative capacity between patients with AD and controls, however. A general linear model examining the effects of socio-demographic variables on test performance found that BNT-SA-SF performance was not significantly affected by the socio-demographic characteristics of participants, including age, education, language, or socio-economic status, with the exception that men appear to achieve higher scores than women. Further, an item analysis identified a number of problematic items and suggestions are made concerning how to deal with these in future studies. Preliminary normative data stratified by sex and education are presented. Results support the clinical utility of the BNT-SA-SF as a screening test to aid in the diagnosis of AD from normal aging with older adults in South Africa. This study is a valuable step forward in the ongoing attempt to provide culturally appropriate and valid neuropsychological tests and norms for clinical and research purposes in South Africa. Future studies should examine the functioning of the test in larger samples, representative of the other major population and language groups in South Africa
