When less is more powerful: Shapley value attributed ablation with augmented learning for practical time series sensor data classification.

Time series sensor data classification tasks often suffer from training data scarcity issue due to the expenses associated with the expert-intervened annotation efforts. For example, Electrocardiogram (ECG) data classification for cardio-vascular disease (CVD) detection requires expensive labeling procedures with the help of cardiologists. Current state-of-the-art algorithms like deep learning models have shown outstanding performance under the general requirement of availability of large set of training examples. In this paper, we propose Shapley Attributed Ablation with Augmented Learning: ShapAAL, which demonstrates that deep learning algorithm with suitably selected subset of the seen examples or ablating the unimportant ones from the given limited training dataset can ensure consistently better classification performance under augmented training. In ShapAAL, additive perturbed training augments the input space to compensate the scarcity in training examples using Residual Network (ResNet) architecture through perturbation-induced inputs, while Shapley attribution seeks the subset from the augmented training space for better learnability with the goal of better general predictive performance, thanks to the "efficiency" and "null player" axioms of transferable utility games upon which Shapley value game is formulated. In ShapAAL, the subset of training examples that contribute positively to a supervised learning setup is derived from the notion of coalition games using Shapley values associated with each of the given inputs' contribution into the model prediction. ShapAAL is a novel push-pull deep architecture where the subset selection through Shapley value attribution pushes the model to lower dimension while augmented training augments the learning capability of the model over unseen data. We perform ablation study to provide the empirical evidence of our claim and we show that proposed ShapAAL method consistently outperforms the current baselines and state-of-the-art algorithms for time series sensor data classification tasks from publicly available UCR time series archive that includes different practical important problems like detection of CVDs from ECG data.

Protecting Physical Communications in 5G C-RAN Architectures through Resonant Mechanisms in Optical Media.

Future 5G networks are characterized by three basic ideas: enhanced mobile broadband communications, massive machine-type communications, and ultra-low-latency communications. Any of these requirements needs, to be fulfilled, the implementation of high-efficiency technologies at all levels. This includes some of the costliest mechanisms in terms of computational time and bitrate: information protection solutions. Typical techniques in this area employ complex algorithms and large protocol headers, which strongly reduces the effective baud rate and latency of future 5G networks and communications. This is especially relevant in the access network, which in 5G networks will follow a cloud-based architecture, where thousands of different devices must communicate, before aggregating all those streams to be sent to the backbone. Then, new and more efficient mechanisms are needed in the cloud radio access networks (C-RAN) for future 5G systems. Therefore, in this paper it is proposed a novel information protection scheme for C-RAN architectures based on resonant phenomena in optical fibers communicating the fronthaul and backhaul in 5G networks. Resonant structures and physical nonlinearities generate a chaotic signal which may encrypt and hide at physical level every communication stream in a very efficient manner. To evaluate the proposed mechanism, an experimental validation based on simulation techniques is also described and results discussed.

Data-Driven Automated Cardiac Health Management with Robust Edge Analytics and De-Risking.

Remote and automated healthcare management has shown the prospective to significantly impact the future of human prognosis rate. Internet of Things (IoT) enables the development and implementation ecosystem to cater the need of large number of relevant stakeholders. In this paper, we consider the cardiac health management system to demonstrate that data-driven techniques produce substantial performance merits in terms of clinical efficacy by employing robust machine learning methods with relevant and selected signal processing features. We consider phonocardiogram (PCG) or heart sound as the exemplary physiological signal. PCG carries substantial cardiac health signature to establish our claim of data-centric superior clinical utility. Our method demonstrates close to 85% accuracy on publicly available MIT-Physionet PCG datasets and outperform relevant state-of-the-art algorithm. Due to its simpler computational architecture of shallow classifier with just three features, the proposed analytics method is performed at edge gateway. However, it is to be noted that healthcare analytics deal with number of sensitive data and subsequent inferences, which need privacy protection. Additionally, the problem of healthcare data privacy prevention is addressed by de-risking of sensitive data management using differential privacy, such that controlled privacy protection on sensitive healthcare data can be enabled. When a user sets for privacy protection, appropriate privacy preservation is guaranteed for defense against privacy-breaching knowledge mining attacks. In this era of IoT and machine intelligence, this work is of practical importance, which enables on-demand automated screening of cardiac health under minimizing the privacy breaching risk.

HyRA: A Hybrid Recommendation Algorithm Focused on Smart POI. Ceutí as a Study Scenario.

Nowadays, Physical Web together with the increase in the use of mobile devices, Global Positioning System (GPS), and Social Networking Sites (SNS) have caused users to share enriched information on the Web such as their tourist experiences. Therefore, an area that has been significantly improved by using the contextual information provided by these technologies is tourism. In this way, the main goals of this work are to propose and develop an algorithm focused on the recommendation of Smart Point of Interaction (Smart POI) for a specific user according to his/her preferences and the Smart POIs' context. Hence, a novel Hybrid Recommendation Algorithm (HyRA) is presented by incorporating an aggregation operator into the user-based Collaborative Filtering (CF) algorithm as well as including the Smart POIs' categories and geographical information. For the experimental phase, two real-world datasets have been collected and preprocessed. In addition, one Smart POIs' categories dataset was built. As a result, a dataset composed of 16 Smart POIs, another constituted by the explicit preferences of 200 respondents, and the last dataset integrated by 13 Smart POIs' categories are provided. The experimental results show that the recommendations suggested by HyRA are promising.

Harvesting entropy for random number generation for internet of things constrained devices using on-board sensors.

Entropy in computer security is associated with the unpredictability of a source of randomness. The random source with high entropy tends to achieve a uniform distribution of random values. Random number generators are one of the most important building blocks of cryptosystems. In constrained devices of the Internet of Things ecosystem, high entropy random number generators are hard to achieve due to hardware limitations. For the purpose of the random number generation in constrained devices, this work proposes a solution based on the least-significant bits concatenation entropy harvesting method. As a potential source of entropy, on-board integrated sensors (i.e., temperature, humidity and two different light sensors) have been analyzed. Additionally, the costs (i.e., time and memory consumption) of the presented approach have been measured. The results obtained from the proposed method with statistical fine tuning achieved a Shannon entropy of around 7.9 bits per byte of data for temperature and humidity sensors. The results showed that sensor-based random number generators are a valuable source of entropy with very small RAM and Flash memory requirements for constrained devices of the Internet of Things.

Optimized ECC Implementation for Secure Communication between Heterogeneous IoT Devices.

The Internet of Things is integrating information systems, places, users and billions of constrained devices into one global network. This network requires secure and private means of communications. The building blocks of the Internet of Things are devices manufactured by various producers and are designed to fulfil different needs. There would be no common hardware platform that could be applied in every scenario. In such a heterogeneous environment, there is a strong need for the optimization of interoperable security. We present optimized elliptic curve Cryptography algorithms that address the security issues in the heterogeneous IoT networks. We have combined cryptographic algorithms for the NXP/Jennic 5148- and MSP430-based IoT devices and used them to created novel key negotiation protocol.

Enzymatic membrane reactor for full saccharification of ionic liquid-pretreated microcrystalline cellulose.

Ultrafiltration reactors based on polymeric or ceramic membranes were shown to be suitable catalytic systems for fast enzymatic saccharification of cellulose, allowing the full recovery and reuse of enzymes. By pre-treating cellulose with the IL 1-butyl-3-methylimidazolium chloride, the suitability of this substrate for enzymatic saccharification in a reactor based on polymeric ultrafiltration membranes was demonstrated, leading to 95% cellulose hydrolysis in 4h at 50°C. The filtration process gave a clear glucose solution (up to 113 mM) at constant permeate flow (24.7 L h(-1) m(-2)), allowing the enzyme to be reused for 9 operation cycles under semi-continuous operation, without any loss of enzyme activity. Under continuous operation mode and using ceramic ultrafiltration membranes at different residence times, the enzymatic reactor showed constant profiles in both the permeate flow rate and the glucose concentration, demonstrating the excellent suitability of the proposed approach for the saccharification of cellulose.

IPv6 addressing proxy: mapping native addressing from legacy technologies and devices to the Internet of Things (IPv6).

Sensors utilize a large number of heterogeneous technologies for a varied set of application environments. The sheer number of devices involved requires that this Internet be the Future Internet, with a core network based on IPv6 and a higher scalability in order to be able to address all the devices, sensors and things located around us. This capability to connect through IPv6 devices, sensors and things is what is defining the so-called Internet of Things (IoT). IPv6 provides addressing space to reach this ubiquitous set of sensors, but legacy technologies, such as X10, European Installation Bus (EIB), Controller Area Network (CAN) and radio frequency ID (RFID) from the industrial, home automation and logistic application areas, do not support the IPv6 protocol. For that reason, a technique must be devised to map the sensor and identification technologies to IPv6, thus allowing homogeneous access via IPv6 features in the context of the IoT. This paper proposes a mapping between the native addressing of each technology and an IPv6 address following a set of rules that are discussed and proposed in this work. Specifically, the paper presents a technology-dependent IPv6 addressing proxy, which maps each device to the different subnetworks built under the IPv6 prefix addresses provided by the internet service provider for each home, building or user. The IPv6 addressing proxy offers a common addressing environment based on IPv6 for all the devices, regardless of the device technology. Thereby, this offers a scalable and homogeneous solution to interact with devices that do not support IPv6 addressing. The IPv6 addressing proxy has been implemented in a multi-protocol Sensors 2013, 13 6688 card and evaluated successfully its performance, scalability and interoperability through a protocol built over IPv6.

Evaluation of the impact of furniture on communications performance for ubiquitous deployment of Wireless Sensor Networks in smart homes.

The extensions of the environment with the integration of sensing systems in any space, in conjunction with ubiquitous computing are enabling the so-called Smart Space Sensor Networks. This new generation of networks are offering full connectivity with any object, through the Internet of Things (IoT) and/or the Web, i.e., the Web of Things. These connectivity capabilities are making it feasible to sense the behaviours of people at home and act accordingly. These sensing systems must be integrated within typical elements found at home such as furniture. For that reason, this work considers furniture as an interesting element for the transparent location of sensors. Furniture is a ubiquitous object, i.e., it can be found everywhere at home or the office, and it can integrate and hide the sensors of a network. This work addresses the lack of an exhaustive study of the effect of furniture on signal losses. In addition an easy-to-use tool for estimating the robustness of the communication channel among the sensor nodes and gateways is proposed. Specifically, the losses in a sensor network signal due to the materials found within the communication link are evaluated. Then, this work proposes a software tool that gathers the obtained results and is capable of evaluating the impact of a given set of materials on the communications. This tool also provides a mechanism to optimize the sensor network deployments during the definition of smart spaces. Specifically, it provides information such as: maximum distances between sensor nodes, most suitable type of furniture to integrate sensors, or battery life of sensor nodes. This tool has been validated empirically in the lab, and it is currently being used by several enterprise partners of the Technological Centre of Furniture and Wood in the southeast of Spain.

Architecture for improving terrestrial logistics based on the Web of Things.

Technological advances for improving supply chain efficiency present three key challenges for managing goods: tracking, tracing and monitoring (TTM), in order to satisfy the requirements for products such as perishable goods where the European Legislations requires them to ship within a prescribed temperature range to ensure freshness and suitability for consumption. The proposed system integrates RFID for tracking and tracing through a distributed architecture developed for heavy goods vehicles, and the sensors embedded in the SunSPOT platform for monitoring the goods transported based on the concept of the Internet of Things. This paper presents how the Internet of Things is integrated for improving terrestrial logistics offering a comprehensive and flexible architecture, with high scalability, according to the specific needs for reaching an item-level continuous monitoring solution. The major contribution from this work is the optimization of the Embedded Web Services based on RESTful (Web of Things) for the access to TTM services at any time during the transportation of goods. Specifically, it has been extended the monitoring patterns such as observe and blockwise transfer for the requirements from the continuous conditional monitoring, and for the transfer of full inventories and partial ones based on conditional queries. In definitive, this work presents an evolution of the previous TTM solutions, which were limited to trailer identification and environment monitoring, to a solution which is able to provide an exhaustive item-level monitoring, required for several use cases. This exhaustive monitoring has required new communication capabilities through the Web of Things, which has been optimized with the use and improvement of a set of communications patterns.

[Right atrial thrombus: a rare presentation of plasminogen activator inhibitor deficiency]. / Trombo na aurícula direita: apresentação rara da deficiência do inibidor do ativador do plaminogénio.

Free-floating right atrial thrombi are rare but associated with high mortality. Although advances in echocardiography have improved diagnosis, their management is still the subject of debate. A 24-year-old woman with a history of smoking, obesity and oral contraceptive use presented to the emergency department with dyspnea, cough and hemoptysis. Transthoracic echocardiography revealed a large free-floating cardiac mass occupying the right atrial chamber and restricting tricuspid valve opening. In view of recurrent pulmonary embolism, she was referred for cardiac surgery and the cardiac mass was excised. Anatomopathological analysis revealed an organized and calcified thrombus. Genetic study showed her to be homozygous for the 4G/4G allelic variant of plasminogen activator inhibitor-1 and heterozygous for the allelic variant A1298C of 5,10-methylenetetrahydrofolate reductase.

Non-cardiac comorbidities in the very elderly with acute myocardial infarction: prevalence and influence on management and in-hospital mortality.

INTRODUCTION: Acute myocardial infarction (AMI) in the very elderly is common and is associated with increased mortality. Despite this, the majority of such patients do not receive the most effective cardiovascular therapies. The presence of non-cardiac comorbidities constitutes an additional challenge to the management of AMI in very elderly patients. OBJECTIVE: To determine the prevalence of non-cardiac comorbidities in the very elderly (age > or = 80 years) with AMI and how it influences their management and in-hospital mortality. METHODS: A total of 132 patients consecutively admitted with a diagnosis of AMI from January 2005 to December 2007 were analyzed retrospectively. Two groups were considered: patients with non-cardiac comorbidities (group 1) and those without non-cardiac comorbidities (group 2). Cardiovascular risk factors and non-cardiac comorbidities (anemia, chronic obstructive pulmonary disease, chronic renal failure, cancer, neurologic or psychiatric disorders, and prostatic hyperplasia in men) were recorded. Use of an invasive strategy and the therapy prescribed at discharge were compared between the groups. RESULTS: Non-cardiac comorbidities were found in 56.8% of patients, with the following prevalences: anemia 18.2%; chronic obstructive pulmonary disease 11.4%; chronic renal failure 25.8%; cancer 3.0%; neurologic or psychiatric disorders 11.4%; and prostatic hyperplasia 20.5%. Patients with comorbidities had longer hospital stay than those without (12.1 +/- 5.5 and 10.1 +/- 3.5 days, respectively; p = 0.014). An invasive strategy, with coronary angiography, was used in 12.1% of patients, with no differences between groups (12.3% in patients without comorbidities and 12.0% in those with, p = 0.82). At discharge, more than 70% of the patients were prescribed aspirin, statins and nitrates. With the exception of non-dihydropyridine calcium antagonists, which were more frequently prescribed in patients with comorbidities (15.9% vs. 2.2%; p = 0.04), no other differences in therapy were observed between the two groups. CONCLUSION: In our population of very elderly patients, the prevalence of non-cardiac comorbidities was high (56.8%), but this did not significantly influence the management of these patients.

[Troponins can fool]. / As troponinas também enganam! A propósito de um caso clínico.

The development of troponins dramatically changed the diagnosis of cardiac injury. Cardiac troponins are the most sensitive and specific biochemical markers of myocardial damage. In 2000. it was elaborated the new definition of miocardial infarction that reflected the importance of that biomarker. The rationale of including troponin assay in the diagnosis pathway was based on the assumption that myocardial necrosis, regardless of its magnitude, should be characterized as myocardial infarction. However, if the patient's clinical picture do no match an elevated troponin result we shoud suspect a false positive value caused by analytical interferences. This article ilustrates, by presentation of a case report, that in spite of its importance in the diagnosis of myocardial infarction, troponin positivity should't be the sole criterion for establishing such a diagnosis.

[Pheocromocytoma with negative MIBG]. / Feocromocitoma com MIBG negative.

Pheochomocytomas are catecholamine-releasing tumors derived from chromaffin cells. These kind of tumors occur in less than 1% of the patients evaluated for hypertension. The authors present a case of pheochomocytoma difficult to localize because MIBG scintigraphy was negative and elaborate a review about that subject.

The role of antidiuretic hormone in the pathophysiology and treatment of heart failure.

Heart failure (HF) is still one of the most important causes of morbidity and mortality worldwide. Neurohormonal changes appear to play an important role in the development and continuation of HF. Among the mediators responsible for these changes, antidiuretic hormone (ADH) is probably the least known. However, elevated concentrations of ADH are frequently found in this syndrome and have prognostic value in addition to known biomarkers. Recent experimental studies and clinical trials have aroused interest in the possible benefits of ADH receptor antagonists. This article reviews the pathophysiological mechanisms of ADH in HF and the latest advances in ADH antagonism in the therapeutic management of HF.

Evaluación urodinámica de la incontinencia urinaria de esfuerzo en el Hospital Guillermo Almenara Irigoyen / Urodinamic evaluation of urinary incontinence at hospital Guillermo Almenara Yrigoyen

Se presentan 15 casos de pacientes con diagnóstico clínico de I.U.E., sometidos a evaluación Urodinámica, en lo que 4 resultados urodinámicos daban diagnóstico de IU mixta, vejiga sensitiva y micción por Rebosamiento. Se hizo evaluación post-operatoria en 4 pacientes y se hizo el valor predicativo entre diagnóstico clínico y urodinámico, encontrándose la importancia de la evaluación urodinámica previa en casos de IUE clínica. Un caso con diagnóstico clínico de vejiga inestable se corroboró por examen urodinámico.

Incidencia de uretritis por chlamydia trachomatis en varones / Incidence of urethritis by chlamydia in males

En 71 pacientes varones en el Consultorio Externo de Urología y Laboratorio del Hospital Nacional "Guillermo Almenara Yrigoyen" por disuria, ardor o secreción uretral, se encontró al examen directo de frotis uretral Chlamydia Trachomatis en 24 (33.7%). Chlamydia Trachomatis asociado a Neisseria Gonorrhoeae en 6 (8.4%), Chlamydia Trachomatis postgonocócica en 8 (12.6%) y Chlamydia Trachomatis asociado a otros gérmenes en 13 (18.3%) de pacientes; fueron tratados con dosis única de penicilina clemizol (2 millones de U.I.IM) y tetraciclina (2 gr.día) dirante 10, 20 ó 30 días