Degradation of Superconducting Properties in MgB2 by Formation of the MgB4 Phase

Superconducting MgB₂ polycrystalline samples have been fabricated under two different conditions in order to determine the effect of MgB₄ phase. A series of samples was placed in an α-alumina container closed with a cup and fired under high purity argon gas. The other series of samples was placed in an α-alumina boot without any lid and fired under similar conditions. For the first series of samples, we have found pure MgB₂ phase formation and a narrow transition width at 0.4 K. For the second series of samples, significant amount of MgB₄ phase were formed and the T _zero was decreased to 27 K. For both the group of samples magnetization hysteresis loops obtained at various temperature range and applied field up to 2 T. The best J _cmag for the first series of samples was 1.9 × 10⁵ A/cm² at 10 K and 0 T, and for the second series of samples was 0.7 × 10⁴ A/cm² at 10 K and 0 T.     

Predicting peak pinch strength: Artificial neural networks vs. regression

Cumulative trauma disorders (CTDs) of the upper extremities are one of the major ergonomics areas of research. Pinching is a common risk factor associated with the development of hand/wrist CTDs. The capacity standards of peak pinch strength for various postures are needed to design the tasks in harmony with the workers. This paper describes the formulation, building and comparison of pinch strength prediction models that were obtained using two approaches: Statistical and artificial neural networks (ANN). Statistical and ANN models were developed to predict the peak chuck pinch strength as a function of different combinations of five elbow and seven shoulder flexion angles, and several anthropometric and physiological variables. The two modeling approaches were compared. The results indicate ANN models to provide more accurate predictions over the standard statistical models.     

Electrochemical synthesis of EDOT–ECZ–EDOT copolymer on carbon fiber micro-electrodes

3,6 bis(3,4-ethylenedioxythiophenyl)-9-Ethylcarbazole (EDOT-ECZ-EDOT or EEE) films are coated electrochemically onto carbon fiber micro-electrodes. Deposition conditions on the electroactivity of the resulting polymers are studied. Structural studies of the polymers have been conducted using different techniques such as cyclic voltammetry, ATR-FTIR, scanning electron microscopy and four-point probe conductivity.     

新疆地区密点麻蜥不同亚种体与尾中14种元素分析比较

用原子吸收分光光度计测定了新疆地区密点麻蜥不同亚种体与尾中14种元素的含量，发现其K、Ca、Mg、Fe、Zn等元素的含量都比较丰富；有毒元素Pb含量均较低：仅在叶城亚种体中含有Cd，且含量极低；密点麻蜥不含有Co、Ni，并讨论了这些元素与其药用机理的关系，为密点麻蜥的进一步开发利用提供一定的科学依据。     

Relation of direct hospitalization costs with length of stay

OBJECTIVE: Our main objective is to analyse to the relationship between the direct cost of a hospitalary discharge and the length of stay controlling for other care variables. METHODS: Analysis of the direct costs of pharmacy, laboratory, pathology and radiology tests of the 21,883 discharged patients in two Barcelona hospitals during 1993, in relationship to care variables contained in the basic minimum data set for discharged patient (BMDSDP). Using both hospital information systems in which are detailed the complete activity carried out and the assignment of unitary costs by means of different methods adapted to the available information, the direct cost is built up for patient and it is assembled by DRG. With the direct cost information and the care variables of the BMDSDP, a simple linear regression (least squared method) is carried out. RESULTS: The average direct cost is up to 31,533 pesetas. The regression by least squared method explains 70% of the variance (R2) and the variables with higher explanatory power are the length of stay and the relative weight of average DRG direct costs, that acts like variable of adjustment. CONCLUSIONS: The variability of the direct cost is explained principally by the length of stay. In addition, the length of stay is also very important on explaining the internal variability of DRG direct cost.     

Comparison of Distance Measures for Planar Curves

The Hausdorff distance is a very natural and straightforward distance measure for comparing geometric shapes like curves or other compact sets. Unfortunately, it is not an appropriate distance measure in some cases. For this reason, the Fréchet distance has been investigated for measuring the resemblance of geometric shapes which avoids the drawbacks of the Hausdorff distance. Unfortunately, it is much harder to compute. Here we investigate under which conditions the two distance measures approximately coincide, i.e., the pathological cases for the Hausdorff distance cannot occur. We show that for closed convex curves both distance measures are the same. Furthermore, they are within a constant factor of each other for so-called κ-straight curves, i.e., curves where the arc length between any two points on the curve is at most a constant κ times their Euclidean distance. Therefore, algorithms for computing the Hausdorff distance can be used in these cases to get exact or approximate computations of the Fréchet distance, as well.     

A new relational learning system using novel rule selection strategies

This paper describes a new rule induction system, rila, which can extract frequent patterns from multiple connected relations. The system supports two different rule selection strategies, namely the select early and select late strategies. Pruning heuristics are used to control the number of hypotheses generated during the learning process. Experimental results are provided on the mutagenesis and the segmentation data sets. The present rule induction algorithm is also compared to the similar relational learning algorithms. Results show that the algorithm is comparable to similar algorithms.     

Energy-performance trade-offs for spatial access methods on memory-resident data

The proliferation of mobile and pervasive computing devices has brought energy constraints into the limelight. Energy-conscious design is important at all levels of system architecture, and the software has a key role to play in conserving battery energy on these devices. With the increasing popularity of spatial database applications, and their anticipated deployment on mobile devices (such as road atlases and GPS-based applications), it is critical to examine the energy implications of spatial data storage and access methods for memory resident datasets. While there has been extensive prior research on spatial access methods on resource-rich environments, this is, perhaps, the first study to examine their suitability for resource-constrained environments. Using a detailed cycle-accurate energy estimation framework and four different datasets, this paper examines the pros and cons of three previously proposed spatial indexing alternatives from both the energy and performance angles. Specifically, the Quadtree, Packed R-tree, and Buddy-Tree structures are evaluated and compared with a brute-force approach that does not use an index. The results show that there are both performance and energy trade-offs between the indexing schemes for the different queries. The nature of the query also plays an important role in determining the energy-performance trade-offs. Further, technological trends and architectural enhancements are influencing factors on the relative behavior of the index structures. The work in the query has a bearing on how and where (on a mobile client or/and on a server) it should be performed for performance and energy savings. The results from this study will be beneficial for the design and implementation of embedded spatial databases, accelerating their deployment on numerous mobile devices. Received: November 11, 2001 / Accepted: March 12, 2002 Published online: November 14, 2002 This paper is a significantly extended version of preliminary work that appeared in the Proceedings of the Very Large Databases (VLDB) 2001 Conference. The extensions include (i) a comparison of indexing alternatives carrying out the operations in a brute-force manner; (ii) observations showing that datasets do play a role in power consumption; (iii) architectural solutions to address the cache and memory hotspots for energy; and (iv) benefits when off-loading the work to a server over a wireless medium compared to doing everything on the handheld device.