Methodology for Estimating Streamflow by Water Balance and Rating Curve Methods Based on Logistic Regression

Both water balance (WB) and rating curve (RC) are methods for estimating streamflow. The first is mostly used to estimate reservoir outflows, while the second is usually adopted in hydrometeorological network streamflow gauges. While WB uses hourly collected data, the RC estimates streamflow using current water level and extrapolation techniques. The objective of this study was to analyze variations in the reservoir’s hourly outflow at Queimado Hydroelectric Power Plant (HPP Queimado) and to propose a method to evaluate whether the estimate of the daily outflows, obtained by the WB method, is similar to the flow values obtained at a conventional station. The logistic regression (LR) model was used because it is a method that adopts binary, categorically dependent variables to identify the event of interest. The results showed that the values of streamflow, obtained from an average of two daily readings, were a good representation of the flows in the region. The LR was able to identify atypical data, especially in the rainy season. This means that data consistency analysis can be faster and safer, when adequately employed and considering the proposed conditions, contributing to both management policies and the management of water resources.

     

OWL‐based acquisition and editing of computer‐interpretable guidelines with the CompGuide editor

Computer‐Interpretable Guidelines (CIGs) are the dominant medium for the delivery of clinical decision support, given the evidence‐based nature of their source material. Therefore, these machine‐readable versions have the ability to improve practitioner performance and conformance to standards, with availability at the point and time of care. The formalisation of Clinical Practice Guideline knowledge in a machine‐readable format is a crucial task to make it suitable for the integration in Clinical Decision Support Systems. However, the current tools for this purpose reveal shortcomings with respect to their ease of use and the support offered during CIG acquisition and editing. In this work, we characterise the current landscape of CIG acquisition tools based on the properties of guideline visualisation, organisation, simplicity, automation, manipulation of knowledge elements, and guideline storage and dissemination. Additionally, we describe the CompGuide Editor, a tool for the acquisition of CIGs in the CompGuide model for Clinical Practice Guidelines that also allows the editing of previously encoded guidelines. The Editor guides the users throughout the process of guideline encoding and does not require proficiency in any programming language. The features of the CIG encoding process are revealed through a comparison with already established tools for CIG acquisition.     

Piperacillin/tazobactam‐induced neurotoxicity in a hemodialysis patient: A case report

Antibiotics are potentially a cause of neurotoxicity in dialysis patients, the most common are the beta‐lactams as ceftazidime and cefepime, and few cases have been reported after piperacillin/tazobactam use. This report presents a case of a hypertensive and diabetic 67‐year‐old woman in regular hemodialysis, which previously had a stroke. She was hospitalized presenting pneumonia, which was initially treated with cefepime. Two days after treatment, she presented dysarthria, left hemiparesis, ataxia, and IX and X cranial nerves paresis. Computed tomography showed no acute lesions and cefepime neurotoxicity was hypothesized, and the antibiotic was replaced by piperacillin/tazobactam. The neurologic signs disappeared; however, 4 days after with piperacillin/tazobactam treatment, the neurological manifestations returned. A new computed tomography showed no new lesions, and the second antibiotic regimen withdrawn. After two hemodialysis sessions, the patient completely recovered from neurological manifestations. The patient presented sequentially neurotoxicity caused by two beta‐lactams antibiotics. This report meant to alert clinicians that these antibiotics have dangerous neurological effects in chronic kidney disease patients.     

The influence of magnetron sputtered silver and titanium coatings on the compaction and properties of surface modified PM Ti-48Al powders

Thin layers of silver and titanium were deposited onto commercial Ti–₄₈Al particles by magnetron sputtering prior to their consolidation by hot isostatic pressing and subsequent heat treatment. Based on picnometry and electron probe microanalysis results, average values of 1.5 and 2.5 at.%, respectively, were obtained for the silver and titanium contents in the coated particles. The surface modified Ti–₄₈Al particles exhibited improved sintering ability than the unmodified ones. The consolidated samples have duplex microstructures formed by γ-TiAl and γ-TiAl + α₂-Ti₃Al grains. Ag-rich nanoprecipitates were detected in the microstructure of the compacted Ti-₄₈Al + Ag sample. The coatings are no longer visible at the grains boundaries after a subsequent homogenization heat treatment at 1200°C. The highest values of hardness and Young’s modulus were obtained for the Ti–₄₈Al + Ag sample, associated with a higher density and a lower percentage of pores.     

Evaluation of the thermal and mechanical properties of poly(ε‐caprolactone), low‐density polyethylene,and their blends

The thermal and mechanical properties of low‐density polyethylene (LDPE), poly(ε‐caprolactone) (PCL), and their blends were evaluated. Differential scanning calorimetry showed that increasing the PCL content of the blend did not change the LDPE melting temperature, but reduced the crystallinity by up to 16.8%. This behavior was related to interactions between the PCL chains and the crystalline phase of LDPE. Tensile strength and elongation at break values for the blends were lower than those for the pure polymers, which suggested an incompatibility between the polymers. The values for Young's modulus under tensile increased when PCL was added to LDPE. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 91:3909–3914, 2004     

Development and implementation of clinical guidelines: An artificial intelligence perspective

Clinical practice guidelines in paper format are still the preferred form of delivery of medical knowledge and recommendations to healthcare professionals. Their current support and development process have well identified limitations to which the healthcare community has been continuously searching solutions. Artificial intelligence may create the conditions and provide the tools to address many, if not all, of these limitations.. This paper presents a comprehensive and up to date review of computer-interpretable guideline approaches, namely Arden Syntax, GLIF, PROforma, Asbru, GLARE and SAGE. It also provides an assessment of how well these approaches respond to the challenges posed by paper-based guidelines and addresses topics of Artificial intelligence that could provide a solution to the shortcomings of clinical guidelines. Among the topics addressed by this paper are expert systems, case-based reasoning, medical ontologies and reasoning under uncertainty, with a special focus on methodologies for assessing quality of information when managing incomplete information. Finally, an analysis is made of the fundamental requirements of a guideline model and the importance that standard terminologies and models for clinical data have in the semantic and syntactic interoperability between a guideline execution engine and the software tools used in clinical settings. It is also proposed a line of research that includes the development of an ontology for clinical practice guidelines and a decision model for a guideline-based expert system that manages non-compliance with clinical guidelines and uncertainty.     

Enhancing thermal and dynamic-mechanical properties of epoxy reinforced by amino-functionalized microcrystalline cellulose

In this study, microcrystalline cellulose (MCC) was chemically modified with 3-(aminopropyl)triethoxysilane and added to epoxy to improve chemical, thermal and dynamic-mechanical characteristics of the composites. The composites were manufactured aided by sonication with 1.0%, 2.5%, or 5.0% wt/wt of untreated MCC or amino-functionalized MCC (MCC-Si). The epoxy/MCC-Si composites showed a decrease in the ─OH band by Fourier-transform infrared spectroscopy, and X-ray diffraction analysis indicated better dispersion. The incorporation of MCC-Si in epoxy resin decreased the heat of reaction, increased activation energy values (E_a) and pre-exponential factor (A), and did not affect thermal degradation. All conversion degree (α) versus temperature curves for the composites showed a sigmoidal shape. MCC-Si composites showed better dynamic-mechanical properties than the MCC counterparts, and the functionalization effect was evidenced in storage modulus (E') and loss modulus (E"). At 2.5% wt/wt of MCC-Si content an increase of 119% in E' at the glassy region, 127% in E' at the rubbery region and 173% in E" was observed compared to the neat resin, whereas the T_g barely changed among samples. Good adhesion between the amino-functionalized MCC and the epoxy matrix was observed at the fracture surface, evidencing that surface modification of MCC improves their chemical interaction.     

Hand gesture recognition from depth and infrared Kinect data for CAVE applications interaction

This paper presents a real-time framework that combines depth data and infrared laser speckle pattern (ILSP) images, captured from a Kinect device, for static hand gesture recognition to interact with CAVE applications. At the startup of the system, background removal and hand position detection are performed using only the depth map. After that, tracking is started using the hand positions of the previous frames in order to seek for the hand centroid of the current one. The obtained point is used as a seed for a region growing algorithm to perform hand segmentation in the depth map. The result is a mask that will be used for hand segmentation in the ILSP frame sequence. Next, we apply motion restrictions for gesture spotting in order to mark each image as a ‘Gesture’ or ‘Non-Gesture’. The ILSP counterparts of the frames labeled as “Gesture” are enhanced by using mask subtraction, contrast stretching, median filter, and histogram equalization. The result is used as the input for the feature extraction using a scale invariant feature transform algorithm (SIFT), bag-of-visual-words construction and classification through a multi-class support vector machine (SVM) classifier. Finally, we build a grammar based on the hand gesture classes to convert the classification results in control commands for the CAVE application. The performed tests and comparisons show that the implemented plugin is an efficient solution. We achieve state-of-the-art recognition accuracy as well as efficient object manipulation in a virtual scene visualized in the CAVE.     

A dynamic default revision mechanism for speculative computation

In this work a default revision mechanism is introduced into speculative computation to manage incomplete information. The default revision is supported by a method for the generation of default constraints based on Bayesian networks. The method enables the generation of an initial set of defaults which is used to produce the most likely scenarios during the computation, represented by active processes. As facts arrive, the Bayesian network is used to derive new defaults. The objective with such a new dynamic mechanism is to keep the active processes coherent with arrived facts. This is achieved by changing the initial set of default constraints during the reasoning process in speculative computation. A practical example in clinical decision support is described.