Temperament and character modify risk of drug addiction and influence choice of drugs.

BACKGROUND: Drug addiction and alcoholism involve a complex etiopathogenesis with a variable degree of risk contributions from the host (person), environment, and addictive substances. In this work, temperament and character features of individuals addicted to opiates or alcohol are compared with normal controls to study personality factors in the overall risk for drug addiction. METHODS: The study was done in a permissive environment, with easy access to alcohol and heroin, which facilitated analyses of personality factors in drug choice. Participants included 412 consecutive patients (312 opiate addicts, 100 alcohol addicts) treated at the Specialized Hospital for Chemical Dependency in Belgrade, Serbia, and a community sample of 346 controls. RESULTS: Opiate addicts manifested antisocial temperament configuration (high Novelty Seeking, low Reward Dependence) coupled with high Self-transcendence (ie, susceptibility to fantasy and imagination). Alcohol addicts manifested sensitive temperament configuration (high Novelty Seeking coexisting with high Harm Avoidance). Immature personality was observed far more frequently in opiate addicts than in alcoholics or normals. CONCLUSIONS: Novelty Seeking appears to be a general risk factor for drug addiction. High Harm Avoidance appears to channel individuals with high Novelty Seeking towards alcoholism. Immature character traits and probable Personality Disorder increase the risk of illegal drugs. Based on equivalent research in nonpermissive environments, at least a portion of our opiate addicts could have developed alcoholism instead in environments with more limited access to opiates. Personality factors provide useful guidelines for preventive work with young individuals with personality risk factors for drug addiction.

An approach to a comprehensive test framework for analysis and evaluation of text line segmentation algorithms.

The paper introduces a testing framework for the evaluation and validation of text line segmentation algorithms. Text line segmentation represents the key action for correct optical character recognition. Many of the tests for the evaluation of text line segmentation algorithms deal with text databases as reference templates. Because of the mismatch, the reliable testing framework is required. Hence, a new approach to a comprehensive experimental framework for the evaluation of text line segmentation algorithms is proposed. It consists of synthetic multi-like text samples and real handwritten text as well. Although the tests are mutually independent, the results are cross-linked. The proposed method can be used for different types of scripts and languages. Furthermore, two different procedures for the evaluation of algorithm efficiency based on the obtained error type classification are proposed. The first is based on the segmentation line error description, while the second one incorporates well-known signal detection theory. Each of them has different capabilities and convenience, but they can be used as supplements to make the evaluation process efficient. Overall the proposed procedure based on the segmentation line error description has some advantages, characterized by five measures that describe measurement procedures.

Basic test framework for the evaluation of text line segmentation and text parameter extraction.

Text line segmentation is an essential stage in off-line optical character recognition (OCR) systems. It is a key because inaccurately segmented text lines will lead to OCR failure. Text line segmentation of handwritten documents is a complex and diverse problem, complicated by the nature of handwriting. Hence, text line segmentation is a leading challenge in handwritten document image processing. Due to inconsistencies in measurement and evaluation of text segmentation algorithm quality, some basic set of measurement methods is required. Currently, there is no commonly accepted one and all algorithm evaluation is custom oriented. In this paper, a basic test framework for the evaluation of text feature extraction algorithms is proposed. This test framework consists of a few experiments primarily linked to text line segmentation, skew rate and reference text line evaluation. Although they are mutually independent, the results obtained are strongly cross linked. In the end, its suitability for different types of letters and languages as well as its adaptability are its main advantages. Thus, the paper presents an efficient evaluation method for text analysis algorithms.

Chopper stabilized low resistance comparator.

The paper describes an improvement of the chopper method for elimination of parasitic voltages in a low resistance comparison and measurement procedure. The basic circuit diagram along with a short description of the working principle are presented and the appropriate low resistance comparator prototype was designed and realized. Preliminary examinations confirm the possibility of measuring extremely low voltages. Very high accuracy in resistance comparison and measurement is achieved (0.08 ppm for 1,000 attempts). Some special critical features in the design are discussed and solutions for overcoming the problems are described.

Hardware and Software of a Bipolar Current Source Controlled by PC.

This paper describes a realization of a bipolar current source developed by the paper's authors. The source is intended for use in galvanic and other industrial plants, where a pulse-reverse current supply (with the desired shape in time) is required. A prototype of the device, which provides the outcome current intensity up to ± 50 A, has been constructed. The hardware of the source consists of a Pentium IV PC, a commercial ADDA converter, an interface of authors' original construction as well as a current regulator. The application software is developed using a commercial packet LabView as the basis.