Web-assisted tunneling in the kicked harmonic oscillator

We show that heating of harmonically trapped ions by periodic delta kicks is dramatically enhanced at isolated values of the Lamb-Dicke parameter. At these values, quasienergy eigenstates localized on island structures undergo avoided crossings with extended web-states.Comment: 4 pages, 4 figures. Accepted for publication in Phys. Rev. Let

Cancer/Testis Antigen MAGE-C1/CT7: New Target for Multiple Myeloma Therapy

Cancer/Testis Antigens (CTAs) are a promising class of tumor antigens that have a limited expression in somatic tissues (testis, ovary, fetal, and placental cells). Aberrant expression of CTAs in cancer cells may lead to abnormal chromosome segregation and aneuploidy. CTAs are regulated by epigenetic mechanisms (DNA methylation and acetylation of histones) and are attractive targets for immunotherapy in cancer because the gonads are immune privileged organs and anti-CTA immune response can be tumor-specific. Multiple myeloma (MM) is an incurable hematological malignancy, and several CTAs have been detected in many MM cell lines and patients. Among CTAs expressed in MM we must highlight the MAGE-C1/CT7 located on the X chromosome and expressed specificity in the malignant plasma cells. MAGE-C1/CT7 seems to be related to disease progression and functional studies suggests that this CTA might play a role in cell cycle and mainly in survival of malignant plasma cells, protecting myeloma cells against spontaneous as well as drug-induced apoptosis

Throughput limits of two 802.15.4 wireless networks applications for signal acquisition

This work describes the development and test of a wireless sensor network used by a biomedical signal monitoring system. Data communication is based on a body area network (BAN) materialized as a wireless network in two versions, one based on the 802.15.4 specification and another on a higher-level Zigbee protocol. The system was developed using the Jennic JN5148 microcontroller, Jennics ZBPro stack and the JenOs RT kernell. The final system was tested with the devices at different distances, and with a varying number of sensor nodes communicating simultaneously. For each of these combinations the signal quality and frequency of communication errors were recorded. The version implemented using Zigbee protocol was able to acquire and send sensor signals at a sample rate of 7 kSamples/s (12-bit samples, final net rate of 84 kbps) with a percentage of lost frames below 4%. It was also shown that the system supports simultaneous communication of three sensor nodes at 3 kS/s (36 kbps) each, with a percentage of losses of less than 4%. These results are important since they support the possibility of having several sensors acquiring fast biomedical signals and sending them to a central unit in real time.Fundação para a Ciência e a Tecnologia (FCT) - Projeto Bioswi

Meta-learning recommendation of default hyper-parameter values for SVMs in classifications tasks

Machine learning algorithms have been investigated in several scenarios, one of them is the data classification. The predictive performance of the models induced by these algorithms is usually strongly affected by the values used for their hyper-parameters. Different approaches to define these values have been proposed, like the use of default values and optimization techniques. Although default values can result in models with good predictive performance, different implementations of the same machine learning algorithms use different default values, leading to models with clearly different predictive performance for the same dataset. Optimization techniques have been used to search for hyper-parameter values able to maximize the predictive performance of induced models for a given dataset, but with the drawback of a high computational cost. A compromise is to use an optimization technique to search for values that are suitable for a wide spectrum of datasets. This paper investigates the use of meta-learning to recommend default values for the induction of Support Vector Machine models for a new classification dataset. We compare the default values suggested by the Weka and LibSVM tools with default values optimized by meta-heuristics on a large range of datasets. This study covers only classification task, but we believe that similar ideas could be used in other related tasks. According to the experimental results, meta-models can accurately predict whether tool suggested or optimized default values should be used.CAPESCNPqSão Paulo Research Foundation (FAPESP) (grant#2012/23114-9

Textile sensors for ECG and respiratory frequency on swimsuits

Swimming constitutes one of the most demanding sports regarding technique. Years of training are necessary to master each one of the four styles. An important improvement and help for trainers would be a swimsuit that could provide information during training. This paper presents the research undertaken to develop textile sensors that will be used in a swimsuit. This paper will address ECG and respiratory frequency sensors and respective signals. The behaviour of the proposed sensors in different conditions (dry and wet environments) will be presented and discussed. The influence of movement on the signal quality and further interpretation, both by the muscular electrical signals as well as by the displacement of the electrodes, will be addressed. Other very important issue in swimming is drag. One approach that can reduce total drag consists in using compression. However, compressed fabrics will most likely modify the textile sensors’Fundação para a Ciência e a Tecnologia (FCT) - PTDC/EEA-ELC/70803/200