Determination of the mosaic angle distribution of Grafoil platelets using continuous-wave NMR spectra

We described details of a method to estimate with good accuracy the mosaic angle distributions of microcrystallites (platelets) in exfoliated graphite like Grafoil which is commonly used as an adsorption substrate for helium thin films. The method is based on analysis of resonance field shifts in continuous-wave (CW) NMR spectra of $^{3}$He ferromagnetic monolayers making use of the large nuclear polarization of the adsorbate itself. The mosaic angle distribution of a Grafoil substrate analyzed in this way can be well fitted to a gaussian form with a $27.5\pm2.5$ deg spread. This distribution is quite different from the previous estimation based on neutron scattering data which showed an unrealistically large isotropic powder-like component.Comment: 6 pages, 5 figure

Additions to the avifauna of northern Angola I.

During the course of a year\u27s visit to Angola for the Peabody Museum in 1957-58 by one of us (Heinrich) a number of interesting new records were made…

Comments on the avifauna of Tanzania, II

Buccanodon olivaceum ulugurensis and Viridubucco leucomystax meridionalis (both Capitonidae), new subspecies, are described on the basis of morphological characters. Evidence is presented that Dendropicos fuscescens (Vieillot) and Dendropicos lafresnayi Malherbe ( = D. f. lafresnayi Malherbe) are distinct taxa. The distribution of Smithornis capensis (Smith) is redefined based on an examination of a large series of specimens from eastern Africa. Smithornis capensis meinertzhageni van Someren, S. c. suahelicus Grote, S. c. shimba van Someren, and S. c. chyulu van Someren are reinstated as valid subspecies and a key to their identification is given. Macrodipteryx longipennis (Shaw) is recorded as new to Tanzania. New records of Modulatrix stictigula stictigula (Reichenow) from the Uzungwa Plateau show that this subspecies has a disjunct range in south-central Tanzania. Species and subspecies representing extensions of geographic range in Tanzania are Caprimulgus poliocephalus Ruppell, Tricholaema lacrymosum lacrymosum Cabanis and T. I. ruahae Neumann. Field data from specimens of Alethe fulleborni (Reichenow) reveal that the breeding season coincides with the rainy season, October to March. Call notes and behavior of this species, based on field observations, are also recorded

Comments on the avifauna of Tanzania I

In 1961-63 Gerd H. Heinrich and his wife, accompanied during the first year by their son Bernd Heinrich, carried out an ornithological expedition through Tanzania…

Additions to the avifauna of northern Angola II

The present publication is a continuation of the report published in Postilla no. 47, 1960. It refers to the same collection, procured by Mr. and Mrs. Heinrich for the Peabody Museum during the course of their expedition to Angola in 1957-1958…

Origin of adiabatic and non-adiabatic spin transfer torques in current-driven magnetic domain wall motion

A consistent theory to describe the correlated dynamics of quantum mechanical itinerant spins and semiclassical local magnetization is given. We consider the itinerant spins as quantum mechanical operators, whereas local moments are considered within classical Lagrangian formalism. By appropriately treating fluctuation space spanned by basis functions, including a zero-mode wave function, we construct coupled equations of motion for the collective coordinate of the center-of-mass motion and the localized zero-mode coordinate perpendicular to the domain wall plane. By solving them, we demonstrate that the correlated dynamics is understood through a hierarchy of two time scales: Boltzmann relaxation time when a non-adiabatic part of the spin-transfer torque appears, and Gilbert damping time when adiabatic part comes up.Comment: 4 pages, 2 figure

Razor: Mining distance-constrained embedded subtrees

Our work is focused on the task of mining frequent subtrees from a database of rooted ordered labelled subtrees. Previously we have developed an efficient algorithm, MB3 [12], for mining frequent embedded subtrees from a database of rooted labeled and ordered subtrees. The efficiency comes from the utilization of a novel Embedding List representation for Tree Model Guided (TMG) candidate generation. As an extension the IMB3 [13] algorithm introduces the Level of Embedding constraint. In this study we extend our past work by developing an algorithm, Razor, for mining embedded subtrees where the distance of nodes relative to the root of the subtree needs to be considered. This notion of distance constrained embedded tree mining will have important applications in web information systems, conceptual model analysis and more sophisticated ontology matching. Domains representing their knowledge in a tree structured form may require this additional distance information as it commonly indicates the amount of specific knowledge stored about a particular concept within the hierarchy. The structure based approaches for schema matching commonly take the distance among the concept nodes within a sub-structure into account when evaluating the concept similarity across different schemas. We present an encoding strategy to efficiently enumerate candidate subtrees taking the distance of nodes relative to the root of the subtree into account. The algorithm is applied to both synthetic and real-world datasets, and the experimental results demonstrate the correctness and effectiveness of the proposed technique

SEQUEST: Mining frequent subsequences using DMA strips

Sequential patterns exist in data such as DNA string databases, occurrences of recurrent illness, etc. In this study, we present an algorithm, SEQUEST, to mine frequent subsequences from sequential patterns. The challenges of mining a very large database of sequences is computationally expensive and require large memory space. SEQUEST uses a Direct Memory Access Strips (DMA-Strips) structure to efficiently generate candidate subsequences. DMA-Strips structure provides direct access to each item to be manipulated and thus is optimized for speed and space performance. In addition, the proposed technique uses a hybrid principle of frequency counting by the vertical join approach and candidate generation by structure guided method. The structure guided method is adapted from the TMG approach used for enumerating subtrees in our previous work [8]. Experiments utilizing very large databases of sequences which compare our technique with the existing technique, PLWAP [4], demonstrate the effectiveness of our proposed technique

Diagnosis of hypoglycemic episodes using a neural network based rule discovery system

Hypoglycemia or low blood glucose is dangerous and can result in unconsciousness, seizures and even death for Type 1 diabetes mellitus (T1DM) patients. Based on the T1DM patients’ physiological parameters, corrected QT interval of the electrocardiogram (ECG) signal, change of heart rate, and the change of corrected QT interval, we have developed a neural network based rule discovery system with hybridizing the approaches of neural networks and genetic algorithm to identify the presences of hypoglycemic episodes for TIDM patients. The proposed neural network based rule discovery system is built and is validated by using the real T1DM patients’ data sets collected from Department of Health, Government of Western Australia. Experimental results show that the proposed neural network based rule discovery system can achieve more accurate results on both trained and unseen T1DM patients’ data sets compared with those developed based on the commonly used classification methods for medical diagnosis, statistical regression, fuzzy regression and genetic programming. Apart from the achievement of these better results, the proposed neural network based rule discovery system can provide explicit information in the form of production rules which compensate for the deficiency of traditional neural network method which do not provide a clear understanding of how they work in prediction as they are in an implicit black-box structure. This explicit information provided by the product rules can convince medical doctors to use the neural networks to perform diagnosis of hypoglycemia on T1DM patients