A spectral clustering algorithm for manufacturing cell formation

A graph clustering algorithm constructs groups of closely related parts and machines separately. After they are matched for the least intercell moves, a refining process runs on the initial cell formation to decrease the number of intercell moves. A simple modification of this main approach can deal with some practical constraints, such as the popular constraint of bounding the maximum number of machines in a cell. Our approach makes a big improvement in the computational time. More importantly, improvement is seen in the number of intercell moves when the computational results were compared with best known solutions from the literature. (C) 2009 Elsevier Ltd. All rights reserved.

Political Parties and Governors as Determinants of Legislative Behavior in Brazil`s Chamber of Deputies, 1988-2006

This article examines the relative importance of regional and national forces in shaping the behavior of Brazilian legislators at the national level. A widely held view is that national legislators respond to state pressures in making decisions, rather than pressures from the national government. Governors not only can influence national debates but also can determine outcomes by exerting control over their states` legislative delegations. This article examines a dataset of all roll-call votes in the Chamber of Deputies between 1989 and 2006 to isolate and evaluate the impact of local pressures on legislative voting. Spanning the terms of five presidents and five different congresses, the data show that the local influence is weaker than the national on the voting decisions of individual legislators and the voting cohesion of state delegations. Alternative institutional resources allow the central government to counteract the centrifugal pressures of federalism and other institutional influences.

Improving Alzheimer`s Disease Diagnosis with Machine Learning Techniques

There is not a specific test to diagnose Alzheimer`s disease (AD). Its diagnosis should be based upon clinical history, neuropsychological and laboratory tests, neuroimaging and electroencephalography (EEG). Therefore, new approaches are necessary to enable earlier and more accurate diagnosis and to follow treatment results. In this study we used a Machine Learning (ML) technique, named Support Vector Machine (SVM), to search patterns in EEG epochs to differentiate AD patients from controls. As a result, we developed a quantitative EEG (qEEG) processing method for automatic differentiation of patients with AD from normal individuals, as a complement to the diagnosis of probable dementia. We studied EEGs from 19 normal subjects (14 females/5 males, mean age 71.6 years) and 16 probable mild to moderate symptoms AD patients (14 females/2 males, mean age 73.4 years. The results obtained from analysis of EEG epochs were accuracy 79.9% and sensitivity 83.2%. The analysis considering the diagnosis of each individual patient reached 87.0% accuracy and 91.7% sensitivity.

Case Series: Sensory Intolerance as a Primary Symptom of Pediatric OCD

Introduction. Marked intolerance or intrusive re-experiencing of ordinary sensory stimuli that in turn drive functionally impairing compulsive behaviors are occasionally seen in voting children with OCD. Methods. We describe a number of children with DSM-IV OCD ascertained from of family genetic study of pediatric OCD, whose intolerance: of ordinary sensory stimuli created significant subjective distress and time-consuming ritualistic behavior that was clinically impairing. Results. In each case these sensory symptoms were the primary presenting symptoms and were experienced in the absence of intrusive thoughts, images, or ideas associated with ""conventional"" OCD symptoms. Conclusions. These symptoms suggest abnormalities in sensory processing and integration in at least a subset of OCD patients. Recognition of these sensory symptoms and sensory-driven behaviors as part of the broad phenotypic Variation in children with OCD could help clinicians more easily identify OCD patients and,facilitate treatment.

Neurodynamics of an election

Variables influencing decision-making in real settings, as in the case of voting decisions, are uncontrollable and in many times even unknown to the experimenter. In this case, the experimenter has to study the intention to decide (vote) as close as possible in time to the moment of the real decision (election day). Here, we investigated the brain activity associated with the voting intention declared 1 week before the election day of the Brazilian Firearms Control Referendum about prohibiting the commerce of firearms. Two alliances arose in the Congress to run the campaigns for YES (for the prohibition of firearm commerce) and NO (against the prohibition of firearm commerce) voting. Time constraints imposed by the necessity of studying a reasonable number (here, 32) of voters during a very short time (5 days) made the EEG the tool of choice for recording the brain activity associated with voting decision. Recent fMRI and EEG studies have shown decision-making as a process due to the enrollment of defined neuronal networks. In this work, a special EEG technique is applied to study the topology of the voting decision-making networks and is compared to the results of standard ERP procedures. The results show that voting decision-making enrolled networks in charge of calculating the benefits and risks of the decision of prohibiting or allowing firearm commerce and that the topology of such networks was vote-(i.e., YES/NO-) sensitive. (C) 2010 Elsevier B.V. All rights reserved.

Two-step tuberculin skin test and booster phenomenon prevalence among Brazilian medical students

SETTING: Five medical schools in three cities in Rio de Janeiro State, Brazil, with different tuberculosis (TB) incidence rates. OBJECTIVE: To evaluate the prevalence of the booster phenomenon and its associated factors in a voting universally BCG-vaccinated TB-exposed population. DESIGN: A two-step tuberculin skin test (TST) was performed among undergraduate medical students. Boosting was defined as an induration >= 10 mm in the second TST (TST2), with an increase of at least 6 mm over the first TST (TST1). The association of boosting with independent variables was evaluated using multivariate analysis. RESULTS: Of the 764 participants (mean age 21.9 +/- 2.7 years), 672 (87.9%) had a BCG scar. The overall booster SUMMARY phenomenon prevalence was 8.4% (95%CI 6.5-10.6). Boosting was associated with TST1 reactions of 1-9 mm (aOR 2.5, 95%CI 1.04-5.9) and with BCG vaccination, mostly after infancy, i.e., after age two years (aOR 9.1, 95%,CI 1.2-70.7). CONCLUSION: The prevalence of the booster phenomenon was high. A two-step TST in young BCG-vaccinated populations, especially in those with TST1 reactions of 1-9 mm, can avoid misdiagnosis as a false conversion and potentially reduce unnecessary treatment for latent TB infection.

Image quality assessment and medical physics evaluation of different portable dental X-ray units

Introduction: Recently developed portable dental X-ray units increase the mobility of the forensic odontologists and allow more efficient X-ray work in a disaster field, especially when used in combination with digital sensors. This type of machines might also have potential for application in remote areas, military and humanitarian missions, dental care of patients with mobility limitation, as well as imaging in operating rooms. Objective: To evaluate radiographic image quality acquired by three portable X-ray devices in combination with four image receptors and to evaluate their medical physics parameters. Materials and methods: Images of five samples consisting of four teeth and one formalin-fixed mandible were acquired by one conventional wall-mounted X-ray unit, MinRay (R) 60/70 kVp, used as a clinical standard, and three portable dental X-ray devices: AnyRay (R) 60 kVp, Nomad (R) 60 kVp and Rextar (R) 70 kVp, in combination with a phosphor image plate (PSP), a CCD, or a CMOS sensor. Three observers evaluated images for standard image quality besides forensic diagnostic quality on a 4-point rating scale. Furthermore, all machines underwent tests for occupational as well as patient dosimetry. Results: Statistical analysis showed good quality imaging for all system, with the combination of Nomad (R) and PSP yielding the best score. A significant difference in image quality between the combination of the four X-ray devices and four sensors was established (p < 0.05). For patient safety, the exposure rate was determined and exit dose rates for MinRay (R) at 60 kVp, MinRay (R) at 70 kVp, AnyRay (R), Nomad (R) and Rextar (R) were 3.4 mGy/s, 4.5 mGy/s, 13.5 mGy/s, 3.8 mGy/s and 2.6 mGy/s respectively. The kVp of the AnyRay (R) system was the most stable, with a ripple of 3.7%. Short-term variations in the tube output of all the devices were less than 10%. AnyRay (R) presented higher estimated effective dose than other machines. Occupational dosimetry showed doses at the operator`s hand being lowest with protective shielding (Nomad (R): 0.1 mu Gy). It was also low while using remote control (distance > 1 m: Rextar (R) < 0.2 mu Gy, MinRay (R) < 0.1 mu Gy). Conclusions: The present study demonstrated the feasibility of three portable X-ray systems to be used for specific indications, based on acceptable image quality and sufficient accuracy of the machines and following the standard guidelines for radiation hygiene. (C) 2010 Elsevier Ireland Ltd. All rights reserved.