Excess volumes and excess viscosities of binary mixtures of some cyclic ethers + bromocyclohexane at 298.15 and 313.15 K

Excess Volumes,V ^E, and excess viscosities, ^E, at 293.15 and 313.15 K are reported for binary mixtures of some cyclic ethers (tetrahydrofuran, tetrahydropyran, 2-methyltetrahydrofuran and 2,5-dimethyltetrahydrofuran) + bromocyclohexane. These properties were obtained from density and viscosity measurements. ^E and ^E show negatives values for all the mixtures.     

Endoscopic sclerotherapy is useful in Dieulafoy''s disease

1.5% Capsaicin (Cap) or Vehicle was respectively used to treat the right or left sciatic nerve in 20 Sprague-Dawley rats. On the seventh day, the 20 rats were at random divided into electroacupuncture (EA) group and non-EA group, the spinal cord corresponding to the afferent segments of sciatic nerve was taken out for observing the changes of acetylcholinesterase (AChE) activity and [3H]-quinuelidinylbenzylate (QNB) binding sites in the spinal dorsal horn (SDH). The results were as follows: (1) EA "Huantiao" could enhance AChE activity in the SDH and decrease [3H]-QNB binding sites; (2) Cap treating sciatice nerve could weaken AChE activity in the SDH and merease [3H]-QNB binding sites; (3) Cap treatment could inhibit or partially inhibit the actions of EA as above. The results indicated that ACh participated in the primary afferent of acupuncture information and might exist in Cap-sensitive neurons.     

Diseases of the digestive system and a system for patient classification: diagnostic-related groups (DRG)

In the last years different classification systems for hospitalized patients have been developed in the United States, that allow to evaluate different aspects of any Hospital: The quality, the efficacy and the efficiency. The classification of "The Diagnosis Related Groups" (DRG) relates the hospitalized patients with the expenses that they generate, and it is the most used in Europe. In the version DRG-All Patient, all the diagnoses and procedures of the hospitalized patients, using the International Classification of Diseases, are divided in to 25 Major Diagnostic Categories (MDC) where each one excludes all the others. We describe the behavior with respect to the age, sex and stay of all the GDR integrated in the CDM 6 and 7: diseases and disorders of the digestive tract, and diseases and disorders of the hepatobiliary system and the pancreas. The study has been carried out with a national data base of two millions of cases seen from 214 acute-care Hospitals. The MDC number 6 is the most frequent, with an important number of patients in the pediatric age; it is more frequent in males; the average stay is 8.59 days and 19 GDR (36.5%) have a variation coefficient greater than one. The other MDC, number 7 is less frequent, the majority of the patients are between 60-80 years of age, the average stay is 12.2 days with a coefficient of variation greater than one in 4 GDR (17.4%). Clinical Services should know the characteristics and behavior of their patients, as well as the comparison with the national data bases. This may allow a control of the quality and the costs by using a common "language" with the managers.     

Simple procedures of choice in multicriteria problems without precise information about the alternatives’ values

The additive model of multiattribute value theory is widely used in multicriteria choice problems. But often it is not easy to obtain precise values for the scaling weights or the alternatives’ value in each function. Several decision rules which require weaker information, such as ordinal information, have been proposed to select an alternative under these circumstances. We propose new decision rules and test them using Monte-Carlo simulation, considering that there is ordinal information both on the scaling weights and on the alternatives’ values. Results show the new rules constitute a good approximation. We provide guidelines about how to use these rules in a context of selecting a subset of the most promising alternatives, considering the contradictory objectives of keeping a low number of alternatives yet not excluding the best one.     

An adaptive, real-time, traffic monitoring system

In this paper we describe a computer vision-based traffic monitoring system able to detect individual vehicles in real-time. Our fully integrated system first obtains the main traffic variables: counting, speed and category; and then computes a complete set of statistical variables. The objective is to investigate some of the difficulties impeding existing traffic systems to achieve balanced accuracy in every condition; i.e. day and night transitions, shadows, heavy vehicles, occlusions, slow traffic and congestions. The system we present is autonomous, works for long periods of time without human intervention and adapts automatically to the changing environmental conditions. Several innovations, designed to deal with the above circumstances, are proposed in the paper: an integrated calibration and image rectification step, differentiated methods for day and night, an adaptive segmentation algorithm, a multistage shadow detection method and special considerations for heavy vehicle identification and treatment of slow traffic. A specific methodology has been developed to benchmark the accuracy of the different methods proposed.     

APROMORE: An advanced process model repository

Business process models are becoming available in large numbers due to their widespread use in many industrial applications such as enterprise and quality engineering projects. On the one hand, this raises a challenge as to their proper management: how can it be ensured that the proper process model is always available to the interested stakeholder? On the other hand, the richness of a large set of process models also offers opportunities, for example with respect to the re-use of existing model parts for new models. This paper describes the functionality and architecture of an advanced process model repository, named APROMORE. This tool brings together a rich set of features for the analysis, management and usage of large sets of process models, drawing from state-of-the art research in the field of process modeling. A prototype of the platform is presented in this paper, demonstrating its feasibility, as well as an outlook on the further development of APROMORE.     

A proposal for student modeling based on ontologies and diagnosis rules

The advances in the educational field and the high complexity of student modeling have provoked it to be one of the aspects more investigated in Intelligent Tutoring Systems (ITSs). The Student Models (SMs) should not only represent the student’s knowledge, but rather they should reflect, as faithfully as possible, the student’s reasoning process. To facilitate this goal, in this article a new approach to student modeling is proposed that benefits from the advantages of Ontological Engineering, advancing in the pursue of a more granular and complete knowledge representation. It’s focused, mainly, on the SM cognitive diagnosis process, and we present a method providing a rich diagnosis about the student’s knowledge state – especially, about the state of learning objectives reached or not. The main goal is to achieve SMs with a good adaptability to the student’s features and a high flexibility for its integration in varied ITSs.