An ice machine adapted into an autonomous photovoltaic system without batteries using a variable-speed drive

The adaptation of a commercially available ice machine for autonomous photovoltaic operation without batteries is presented. In this adaptation a 1040 W(p) photovoltaic array directly feeds a variable-speed drive and a 24 V(dc) source. The drive runs an induction motor coupled by belt-and-pulley to an open reciprocating compressor, while the dc source supplies a solenoid valve and the control electronics. Motor speed and refrigerant evaporation pressure are set aiming at continuously matching system power demand to photovoltaic power availability. The resulting system is a simple integration of robust, standard, readily available parts. It produces 27 kg of ice in a clear-sky day and has ice production costs around US$0.30/kg. Although a few machine features might be specific to Brazil, its technical and economical guidelines are applicable elsewhere. Copyright (C); 2010 John Wiley & Sons, Ltd.

Heuristic methods for the single machine scheduling problem with different ready times and a common due date

The single machine scheduling problem with a common due date and non-identical ready times for the jobs is examined in this work. Performance is measured by the minimization of the weighted sum of earliness and tardiness penalties of the jobs. Since this problem is NP-hard, the application of constructive heuristics that exploit specific characteristics of the problem to improve their performance is investigated. The proposed approaches are examined through a computational comparative study on a set of 280 benchmark test problems with up to 1000 jobs.

Preoperative 6-min walking distance does not predict pulmonary complications in upper abdominal surgery

Background and objective: Field exercise tests have been increasingly used for pulmonary risk assessment. The 6-min walking distance (6MWD) is a field test commonly employed in clinical practice; however, there is limited evidence supporting its use as a risk assessment method in abdominal surgery. The aim was to assess if the 6MWD can predict the development of post-operative pulmonary complications (PPCs) in patients having upper abdominal surgery (UAS). Methods: This prospective cohort study included 137 consecutive subjects undergoing elective UAS. Subjects performed the 6MWD on the day prior to surgery, and their performance were compared with predicted values of 6MWD (p6MWD) using a previously validated formula. PPCs (including pneumonia, tracheobronchitis, atelectasis with clinical repercussions, bronchospasm and acute respiratory failure) were assessed daily by a pulmonologist blinded to the 6MWD results. 6MWD and p6MWD were compared between subjects who developed PPC (PPC group) and those who did not (no PPC group) using Student's t-test. Results: Ten subjects experienced PPC (7.2%) and no significant difference was observed between the 6MWD obtained in the PPC group and no PPC group (466.0 +/- 97.0 m vs 485.3 +/- 107.1 m; P = 0.57, respectively). There was also no significant difference observed between groups for the p6MWD (100.7 +/- 29.1% vs 90.6 -/+ 20.9%; P > 0.05). Conclusions: The results of the present study suggest that the 6-min walking test is not a useful tool to identify subjects with increased risk of developing PPC following UAS.

Safety illusion and error trap in a collectively-operated machine accident

Workplace accidents involving machines are relevant for their magnitude and their impacts on worker health. Despite consolidated critical statements, explanation centered on errors of operators remains predominant with industry professionals, hampering preventive measures and the improvement of production-system reliability. Several initiatives were adopted by enforcement agencies in partnership with universities to stimulate production and diffusion of analysis methodologies with a systemic approach. Starting from one accident case that occurred with a worker who operated a brake-clutch type mechanical press, the article explores cognitive aspects and the existence of traps in the operation of this machine. It deals with a large-sized press that, despite being endowed with a light curtain in areas of access to the pressing zone, did not meet legal requirements. The safety devices gave rise to an illusion of safety, permitting activation of the machine when a worker was still found within the operational zone. Preventive interventions must stimulate the tailoring of systems to the characteristics of workers, minimizing the creation of traps and encouraging safety policies and practices that replace judgments of behaviors that participate in accidents by analyses of reasons that lead workers to act in that manner.

Using Machine Learning Classifiers to Assist Healthcare-Related Decisions: Classification of Electronic Patient Records

Surveillance Levels (SLs) are categories for medical patients (used in Brazil) that represent different types of medical recommendations. SLs are defined according to risk factors and the medical and developmental history of patients. Each SL is associated with specific educational and clinical measures. The objective of the present paper was to verify computer-aided, automatic assignment of SLs. The present paper proposes a computer-aided approach for automatic recommendation of SLs. The approach is based on the classification of information from patient electronic records. For this purpose, a software architecture composed of three layers was developed. The architecture is formed by a classification layer that includes a linguistic module and machine learning classification modules. The classification layer allows for the use of different classification methods, including the use of preprocessed, normalized language data drawn from the linguistic module. We report the verification and validation of the software architecture in a Brazilian pediatric healthcare institution. The results indicate that selection of attributes can have a great effect on the performance of the system. Nonetheless, our automatic recommendation of surveillance level can still benefit from improvements in processing procedures when the linguistic module is applied prior to classification. Results from our efforts can be applied to different types of medical systems. The results of systems supported by the framework presented in this paper may be used by healthcare and governmental institutions to improve healthcare services in terms of establishing preventive measures and alerting authorities about the possibility of an epidemic.

Ventilatory threshold is related to walking tolerance in patients with intermittent claudication

Background: This study assessed the relationship between lower limb hemodynamics and metabolic parameters with walking tolerance in patients with intermittent claudication (IC). Patients and methods: Resting ankle-brachial index (ABI), baseline blood flow (BF), BF response to reactive hyperemia (BFRH), oxygen uptake (VO2), initial claudication distance (ICD) and total walking distance (TWD) were measured in 28 IC patients. Pearson and Spearman correlations were calculated. Results: ABI, baseline BF and BF response to RH did not correlate with ICD or TWD. VO2 at first ventilatory threshold and VO(2)peak were significantly and positively correlated with ICD (r = 0.41 and 0.54, respectively) and TWD (r = 0.65 and 0.71, respectively). Conclusions: VO(2)peak and VO2 at first ventilatory threshold, but not ABI, baseline BF and BFHR were associated with walking tolerance in IC patients. These results suggest that VO2 at first ventilatory threshold may be useful to evaluate walking tolerance and improvements in IC patients.

Stochastic competitive learning in complex networks

Competitive learning is an important machine learning approach which is widely employed in artificial neural networks. In this paper, we present a rigorous definition of a new type of competitive learning scheme realized on large-scale networks. The model consists of several particles walking within the network and competing with each other to occupy as many nodes as possible, while attempting to reject intruder particles. The particle's walking rule is composed of a stochastic combination of random and preferential movements. The model has been applied to solve community detection and data clustering problems. Computer simulations reveal that the proposed technique presents high precision of community and cluster detections, as well as low computational complexity. Moreover, we have developed an efficient method for estimating the most likely number of clusters by using an evaluator index that monitors the information generated by the competition process itself. We hope this paper will provide an alternative way to the study of competitive learning.

Effect of a single session of aerobic walking exercise on arterial pressure in community-living elderly individuals

Several studies have demonstrated that one exercise session (ES) on a cycloergometer or ergometric treadmill causes a reduction in blood pressure (BP). However, there are few similar studies on walking, which is the exercise modality most available to the elderly. We investigated the immediate and 24-h effects of walking on BP in independent, community-living elderly individuals. Volunteers participated in a single ES and resting control session (CS). Before and after each session, BP was measured by auscultatory and oscillometric methods. After each session, 24-h ambulatory blood pressure monitoring was conducted. An accelerometer was installed 48 h before the sessions and left in place for 5 days. The mean volunteer age was 67.7 +/- 3.5 years; 11 were hypertensive patients under treatment, and 12 were normotensive. In the total sample, there were immediate 14mm Hg and 12 mm Hg reductions in systolic BP (SBP) after the ES according to the auscultatory and oscillometric methods, respectively. Diastolic BP (DBP) was reduced by 4 mm Hg after the ES according to both methods. SBP during wakefulness and sleep and DBP during wakefulness were lower after the ES than after the CS (P<0.01), when wakefulness and sleep were determined individually (variable-time pattern) using data from the activity monitors and provided by the volunteers. The variable-time pattern was more effective in detecting reductions in BP than the fixed-time pattern. Hypertension Research (2012) 35, 457-462; doi: 10.1038/hr.2011.227; published online 9 February 2012

Can neuroimaging be used as a support to diagnosis of borderline personality disorder? An approach based on computational neuroanatomy and machine learning

Several recent studies in literature have identified brain morphological alterations associated to Borderline Personality Disorder (BPD) patients. These findings are reported by studies based on voxel-based-morphometry analysis of structural MRI data, comparing mean gray-matter concentration between groups of BPD patients and healthy controls. On the other hand, mean differences between groups are not informative about the discriminative value of neuroimaging data to predict the group of individual subjects. In this paper, we go beyond mean differences analyses, and explore to what extent individual BPD patients can be differentiated from controls (25 subjects in each group), using a combination of automated-morphometric tools for regional cortical thickness/volumetric estimation and Support Vector Machine classifier. The approach included a feature selection step in order to identify the regions containing most discriminative information. The accuracy of this classifier was evaluated using the leave-one-subject-out procedure. The brain regions indicated as containing relevant information to discriminate groups were the orbitofrontal, rostral anterior cingulate, posterior cingulate, middle temporal cortices, among others. These areas, which are distinctively involved in emotional and affect regulation of BPD patients, were the most informative regions to achieve both sensitivity and specificity values of 80% in SVM classification. The findings suggest that this new methodology can add clinical and potential diagnostic value to neuroimaging of psychiatric disorders. (C) 2012 Elsevier Ltd. All rights reserved.

Differences in walking attainment ages between low-risk preterm and healthy full-term infants

Objective: To compare gross motor development of preterm infants (PT) without cerebral palsy with healthy full-term (FT) infants, according to Alberta Infant Motor Scale (AIMS); to compare the age of walking between PT and FT; and whether the age of walking in PT is affected by neonatal variables. Methods: Prospective study compared monthly 101 PT and 52 FT, from the first visit, until all AIMS items had been observed. Results: Mean scores were similarity in their progression, except from the eighth to tenth months. FT infants were faster in walking attainment than PT. Birth weight and length and duration of neonatal nursery stay were related to walking delay. Conclusion: Gross motor development between PT and FT were similar, except from the eighth to tenth months of age. PT walked later than FT infants and predictive variables were birth weight and length, and duration of neonatal intensive unit stay.

Compression stockings have a synergistic effect with walking in the late afternoon to reduce edema of the lower limbs

Aim. The aim of this study was to evaluate whether an association of elastic stockings and walking for a short period in the late afternoon reduces leg edema. Methods. Volume changes of the legs of sixteen patients (32 limbs), who walked on a treadmill for 30 minutes using elastic compression stockings, were analyzed in a quantitative, cross-over randomized (in order of arrival at the clinic) study. They were submitted to volumetry using the water displacement technique and subsequently required to put on 20/30 made-to-measure compression stockings (Sigvaris). The patients walked on a treadmill for 30 minutes and after removing the stockings volumetry of the legs was again performed. Legs were assessed using the CEAP classification and divided into groups. Analysis of variance was used for statistical analysis with an alpha error of 5% being considered acceptable. Results. When participants walked wearing compression stockings, there was a reduction in leg volume. When the CEAP classification was evaluated, it was noted that there was a statistically significant difference for the CEAP C0, C1 and C2 categories of legs using stockings compared to those that did not use. Conclusion. Compression stockings have a synergistic effect with walking in the late afternoon thus reducing edema of the lower limbs. [Int Angiol 2012;31:490-3]