Least squares support vector machines with tuning based on chaotic differential evolution approach applied to the identification of a thermal process

In the past decade, support vector machines (SVMs) have gained the attention of many researchers. SVMs are non-parametric supervised learning schemes that rely on statistical learning theory which enables learning machines to generalize well to unseen data. SVMs refer to kernel-based methods that have been introduced as a robust approach to classification and regression problems, lately has handled nonlinear identification problems, the so called support vector regression. In SVMs designs for nonlinear identification, a nonlinear model is represented by an expansion in terms of nonlinear mappings of the model input. The nonlinear mappings define a feature space, which may have infinite dimension. In this context, a relevant identification approach is the least squares support vector machines (LS-SVMs). Compared to the other identification method, LS-SVMs possess prominent advantages: its generalization performance (i.e. error rates on test sets) either matches or is significantly better than that of the competing methods, and more importantly, the performance does not depend on the dimensionality of the input data. Consider a constrained optimization problem of quadratic programing with a regularized cost function, the training process of LS-SVM involves the selection of kernel parameters and the regularization parameter of the objective function. A good choice of these parameters is crucial for the performance of the estimator. In this paper, the LS-SVMs design proposed is the combination of LS-SVM and a new chaotic differential evolution optimization approach based on Ikeda map (CDEK). The CDEK is adopted in tuning of regularization parameter and the radial basis function bandwith. Simulations using LS-SVMs on NARX (Nonlinear AutoRegressive with eXogenous inputs) for the identification of a thermal process show the effectiveness and practicality of the proposed CDEK algorithm when compared with the classical DE approach.     

The Israeli Diagnostic Center for Malignant Hyperthermia: 7-years' accumulated experience

Malignant hyperthermia (MH), a rare pharmacogenetic trait, can be lethal when susceptible individuals are exposed to triggering agents during general anesthesia. We present our experience with the caffeine-halothane in vitro contracture test (IVCT) for the diagnosis of malignant hyperthermia susceptibility. Out of 75 patients that were referred for consultation to the MH diagnostic center over a period of 7 years, we performed muscle biopsies and IVCT in 21 patients. A total of 6 patients were found to be MH-positive. Appropriate recommendations for future anesthetic management, and additionally, for testing the immediate family were made following a positive diagnosis. Improved familiarity with the syndrome of MH, and performance of IVCT when family or clinical history suggest malignant hyperthermia susceptibility, are imperative measures to prevent the potential fatality associated with this syndrome.     

Malignant hyperthermia

Malignant hyperthermia is a rare autosomal dominant trait that predisposes affected individuals to great danger when exposed to certain anaesthetic triggering agents (such as potent volatile anaesthetics and succinylcholine). A sudden hypermetabolic reaction in skeletal muscle leading to hyperthermia and massive rhabdomyolysis can occur. The ultimate treatment is dantrolene sodium a nonspecific muscle relaxant. Certain precautions should be taken before anaesthesia of patients known to be susceptible to malignant hyperthermia. These include the prohibition of the use of triggering agents, monitoring of central body temperature and expired CO2, and immediate availability of dantrolene. In addition, careful cleansing of the anaesthesia machine of vapours of halogenated agents is recommended. If these measures are taken, the chances of an MH episode are greatly reduced. When malignant hyperthermia-does occur in the operating room, prompt recognition and treatment usually prevent a potentially fatal outcome. The most reliable test to establish susceptibility to malignant hyperthermia is currently the in vitro caffeine-halothane contracture test. It is hoped that in the future a genetic test will be available.     

An analysis of the fees and pending time correlation in Ethereum

Ethereum is a new blockchain-based platform that is also capable of running smart contracts. Despite its increasing popularity, there is a lack of studies on characterizing this system, in special the fees paid by users and the respective delay to confirm the transactions, that is, the pending time. In this sense, we study the main features of Ethereum transactions and evaluate the common belief—for blockchain systems that rely on proof of work—that users who pay higher fees will have their transactions confirmed faster. Specifically, we collect information about 7.2 million of transactions in Ethereum and correlate their pending time to several fee-related features. Moreover, we conduct our study evaluating different ranges of values for the features, such as default and unusual values adopted by users as well as clusters of users with similar behaviors. Our empirical analysis shows strong evidence that there is no clear correlation between fees-related features and the pending time. Overall, we conclude from our investigation that transaction's features, including gas and gas price defined by users, cannot determine the pending time of transactions.     

Energy efficiency and throughput performance of power and rate allocation on incremental decode-and-forward relaying

In this paper we investigate the combination of rate and power allocation techniques in an orthogonal cooperative scheme using infra-structured (fixed) relays, under the incremental decode-and-forward protocol. We consider realistic large scale and small scale path loss models, taking into account the antennas heights and the presence or not of line-of-sight. Results demonstrate that the throughput performance can be significantly increased in the low signal-to-noise ratio (SNR) region due to rate allocation (RA), and in the high SNR region due to power allocation (PA). In addition, we present an energy efficiency analysis which shows that RA is much more efficient than PA over the whole SNR range.     

Multifrequency vibro-acoustography

Elasticity imaging is a burgeoning medical imaging field. Many methods have been proposed that impart a force to tissue and measure the mechanical response. One method, vibro-acoustography, uses the ultrasound radiation force to harmonically vibrate tissue and measure the resulting acoustic emission field with a nearby hydrophone. Another method, vibrometry, uses the ultrasound radiation force accompanied with a measurement of the resulting velocity or displacement of the vibrating tissue or object has also been used for different applications. An extension of the vibro-acoustography method using a multifrequency stress field to vibrate an object is described. The objective of this paper is to present the image formation theory for multifrequency vibro-acoustography. We show that the number of low-frequency components created by this multifrequency method scales with the square of the number of ultrasound sources used. We provide experimental validation of the point-spread function of the multifrequency stress field and show examples of both vibrometry and vibro-acoustography imaging applications. This method holds the potential for a large gain of information with no increase in scanning time compared to conventional vibro-acoustography systems.     

Water Security in an Uncertain Future: Contrasting Realities from an Availability-Demand Perspective

A better understanding of climate change impacts on water security beyond climate variability is of critical importance to tackle water vulnerabilities exacerbated by increasing extreme weather events. Thus, studies on water security in a changing climate help decision-makers to overcome existing political and socioeconomic challenges worldwide. In this study, future water security of two basins was assessed under climate change and demand scenarios by contrasting water demand with probabilistic levels of water availability to identify possible drivers of insecurity. The Guariroba and Jaguari basins are the main sources for supplying water to Campo Grande city and the São Paulo Metropolitan Region, respectively. The physically-based SWAT+?model was calibrated to simulate the basins’ hydrological response to three climate change scenarios from a CMIP6 multimodel ensemble: SSP2-4.5 (medium forcing), SSP3-7.0 (high forcing), and SSP5-8.5 (high forcing). The Guariroba basin already presented scarcity indices close to the security threshold in the baseline period. The imbalance between availability and demand was the main driver of water insecurity in this basin. Despite showing a low scarcity risk in the Jaguari basin in the baseline, this risk considerably increased in the future periods due to a decrease in precipitation. A reduction in water demand of 20% by 2070 was not sufficient to improve water security in both basins. These findings indicate that a lack of policies for adapting demand to a changing availability exacerbates hydrological droughts. More stringent measures to balance water availability and demand are critical for improving water security in an uncertain future.