Parallel Cyclostationarity-Exploiting Algorithm for Energy-Efficient Spectrum Sensing

The evolution of wireless communication systems leads to Dynamic Spectrum Allocation for Cognitive Radio, which requires reliable spectrum sensing techniques. Among the spectrum sensing methods proposed in the literature, those that exploit cyclostationary characteristics of radio signals are particularly suitable for communication environments with low signal-to-noise ratios, or with non-stationary noise. However, such methods have high computational complexity that directly raises the power consumption of devices which often have very stringent low-power requirements. We propose a strategy for cyclostationary spectrum sensing with reduced energy consumption. This strategy is based on the principle that p processors working at slower frequencies consume less power than a single processor for the same execution time. We devise a strict relation between the energy savings and common parallel system metrics. The results of simulations show that our strategy promises very significant savings in actual devices.

Finite time extinction for nonlinear fractional evolution equations and related properties

The finite time extinction phenomenon (the solution reaches an equilibrium after a finite time) is peculiar to certain nonlinear problems whose solutions exhibit an asymptotic behavior entirely different from the typical behavior of solutions associated to linear problems. The main goal of this work is twofold. Firstly, we extend some of the results known in the literature to the case in which the ordinary time derivative is considered jointly with a fractional time differentiation. Secondly, we consider the limit case when only the fractional derivative remains. The latter is the most extraordinary case, since we prove that the finite time extinction phenomenon still appears, even with a non-smooth profile near the extinction time. Some concrete examples of quasi-linear partial differential operators are proposed. Our results can also be applied in the framework of suitable nonlinear Volterra integro-differential equations.

Finite time extinction for nonlinear fractional evolution equations and related properties.

The finite time extinction phenomenon (the solution reaches an equilibrium after a finite time) is peculiar to certain nonlinear problems whose solutions exhibit an asymptotic behavior entirely different from the typical behavior of solutions associated to linear problems. The main goal of this work is twofold. Firstly, we extend some of the results known in the literature to the case in which the ordinary time derivative is considered jointly with a fractional time differentiation. Secondly, we consider the limit case when only the fractional derivative remains. The latter is the most extraordinary case, since we prove that the finite time extinction phenomenon still appears, even with a non-smooth profile near the extinction time. Some concrete examples of quasi-linear partial differential operators are proposed. Our results can also be applied in the framework of suitable nonlinear Volterra integro-differential equations.

Long-evolution ascites in a patient with constrictive pericarditis

Constrictive pericarditis (CP) is an uncommon disease resulting from chronic pericardial inflammation, fibrosis and calcification. Since there are atypical forms of presentation, with subtle or nonexistent cardiorespiratory symptoms, diagnosis may be challenging and difficult. Recurrent ascites in patients with congestive hepatopathy due to constrictive pericarditis is, in most cases, reversible after pericardiectomy. Nevertheless, development of persistent liver dysfunction may be a long-term complication. The present case describes a 23 years old man with growth delay, dyspnoea and long evolution ascites, whose exhaustive etiological investigation led to diagnosis. Afterwards the patient underwent elective surgery with symptom and general condition improvement. Ascites differential diagnosis and its association with constrictive pericarditis are briefly reviewed in this article.

Evolution of classifiers for pitch estimation of piano music using cartesian genetic programming

Pitch Estimation, also known as Fundamental Frequency (F0) estimation, has been a popular research topic for many years, and is still investigated nowadays. The goal of Pitch Estimation is to find the pitch or fundamental frequency of a digital recording of a speech or musical notes. It plays an important role, because it is the key to identify which notes are being played and at what time. Pitch Estimation of real instruments is a very hard task to address. Each instrument has its own physical characteristics, which reflects in different spectral characteristics. Furthermore, the recording conditions can vary from studio to studio and background noises must be considered. This dissertation presents a novel approach to the problem of Pitch Estimation, using Cartesian Genetic Programming (CGP).We take advantage of evolutionary algorithms, in particular CGP, to explore and evolve complex mathematical functions that act as classifiers. These classifiers are used to identify piano notes pitches in an audio signal. To help us with the codification of the problem, we built a highly flexible CGP Toolbox, generic enough to encode different kind of programs. The encoded evolutionary algorithm is the one known as 1 + , and we can choose the value for . The toolbox is very simple to use. Settings such as the mutation probability, number of runs and generations are configurable. The cartesian representation of CGP can take multiple forms and it is able to encode function parameters. It is prepared to handle with different type of fitness functions: minimization of f(x) and maximization of f(x) and has a useful system of callbacks. We trained 61 classifiers corresponding to 61 piano notes. A training set of audio signals was used for each of the classifiers: half were signals with the same pitch as the classifier (true positive signals) and the other half were signals with different pitches (true negative signals). F-measure was used for the fitness function. Signals with the same pitch of the classifier that were correctly identified by the classifier, count as a true positives. Signals with the same pitch of the classifier that were not correctly identified by the classifier, count as a false negatives. Signals with different pitch of the classifier that were not identified by the classifier, count as a true negatives. Signals with different pitch of the classifier that were identified by the classifier, count as a false positives. Our first approach was to evolve classifiers for identifying artifical signals, created by mathematical functions: sine, sawtooth and square waves. Our function set is basically composed by filtering operations on vectors and by arithmetic operations with constants and vectors. All the classifiers correctly identified true positive signals and did not identify true negative signals. We then moved to real audio recordings. For testing the classifiers, we picked different audio signals from the ones used during the training phase. For a first approach, the obtained results were very promising, but could be improved. We have made slight changes to our approach and the number of false positives reduced 33%, compared to the first approach. We then applied the evolved classifiers to polyphonic audio signals, and the results indicate that our approach is a good starting point for addressing the problem of Pitch Estimation.

Measure-valued mass evolution problems with flux boundary conditions and solution-dependent velocities

In this paper we prove well-posedness for a measure-valued continuity equation with solution-dependent velocity and flux boundary conditions, posed on a bounded one-dimensional domain. We generalize the results of an earlier paper [J. Differential Equations, 259 (2015), pp. 10681097] to settings where the dynamics are driven by interactions. In a forward-Euler-like approach, we construct a time-discretized version of the original problem and employ those results as a building block within each subinterval. A limit solution is obtained as the mesh size of the time discretization goes to zero. Moreover, the limit is independent of the specific way of partitioning the time interval [0, T]. This paper is partially based on results presented in Chapter 5 of [Evolution Equations for Systems Governed by Social Interactions, Ph.D. thesis, Eindhoven University of Technology, 2015], while a number of issues that were still open there are now resolved.

Evolution of emerging iPS cell-based therapies for age-related macular degeneration (AMD)

Stem cell-based regenerative medicine is poised to revolutionize the way diseases are treated. In recent years, induced pluripotent stem (iPS) cells, a newly stem cell species, has attracted significant attention. This paper seeks to understand the pathways along which emerging clinical research efforts in the field of iPS cells is evolved. In particular, the empirical case of age-related macular degeneration (AMD) is used, which is the world-pioneering clinical application of iPS cells. In line with the literature, this study explores the interrelations between three different pathways, such as biomedical scientific understanding, development of medical technologies, and learning in clinical practice. For this, a techmining approach is used including co-term, co-citation, and direct citation methods. Scientific publications indexed in the Thomson Reuters' Web of Science and Elsevier's Scopus databases form the basis of the study. This research first explores the iPS cell research landscape through the construction of a co-term map, particularly stressing the location and intensity of disease-tackling efforts; then focus on the evolution of scientific knowledge on AMD through co-citation networks and the main path algorithm on direct citations. At the researcher level, the development of four different research groups working on cell therapies for AMD is evaluated through the software CitNetExplorer. By integrating these approaches, the result shows a wider picture of the complexities inherent in the translation of knowledge into revolutionary clinical methods.

Investigating automated chemical evolution of oil-in-water droplets

One of the main unresolved questions in science is how non-living matter became alive in a process known as abiognesis, which aims to explain how from a primordial soup scenario containing simple molecules, by following a ``bottom up'' approach, complex biomolecules emerged forming the first living system, known as a protocell. A protocell is defined by the interplay of three sub-systems which are considered requirements for life: information molecules, metabolism, and compartmentalization. This thesis investigates the role of compartmentalization during the emergence of life, and how simple membrane aggregates could evolve into entities that were able to develop ``life-like'' behaviours, and in particular how such evolution could happen without the presence of information molecules. Our ultimate objective is to create an autonomous evolvable system, and in order tp do so we will try to engineer life following a ``top-down'' approach, where an initial platform capable of evolving chemistry will be constructed, but the chemistry being dependent on the robotic adjunct, and how then this platform can be de-constructed in iterative operations until it is fully disconnected from the evolvable system, the system then being inherently autonomous. The first project of this thesis describes how the initial platform was designed and built. The platform was based on the model of a standard liquid handling robot, with the main difference with respect to other similar robots being that we used a 3D-printer in order to prototype the robot and build its main equipment, like a liquid dispensing system, tool movement mechanism, and washing procedures. The robot was able to mix different components and create populations of droplets in a Petri dish filled with aqueous phase. The Petri dish was then observed by a camera, which analysed the behaviours described by the droplets and fed this information back to the robot. Using this loop, the robot was then able to implement an evolutionary algorithm, where populations of droplets were evolved towards defined life-like behaviours. The second project of this thesis aimed to remove as many mechanical parts as possible from the robot while keeping the evolvable chemistry intact. In order to do so, we encapsulated the functionalities of the previous liquid handling robot into a single monolithic 3D-printed device. This device was able to mix different components, generate populations of droplets in an aqueous phase, and was also equipped with a camera in order to analyse the experiments. Moreover, because the full fabrication process of the devices happened in a 3D-printer, we were also able to alter its experimental arena by adding different obstacles where to evolve the droplets, enabling us to study how environmental changes can shape evolution. By doing so, we were able to embody evolutionary characteristics into our device, removing constraints from the physical platform, and taking one step forward to a possible autonomous evolvable system.

Local and nonlocal integro-differential reaction-diffusion models for protein dynamics in Alzheimer's disease

In this work, integro-differential reaction-diffusion models are presented for the description of the temporal and spatial evolution of the concentrations of Abeta and tau proteins involved in Alzheimer's disease. Initially, a local model is analysed: this is obtained by coupling with an interaction term two heterodimer models, modified by adding diffusion and Holling functional terms of the second type. We then move on to the presentation of three nonlocal models, which differ according to the type of the growth (exponential, logistic or Gompertzian) considered for healthy proteins. In these models integral terms are introduced to consider the interaction between proteins that are located at different spatial points possibly far apart. For each of the models introduced, the determination of equilibrium points with their stability and a study of the clearance inequalities are carried out. In addition, since the integrals introduced imply a spatial nonlocality in the models exhibited, some general features of nonlocal models are presented. Afterwards, with the aim of developing simulations, it is decided to transfer the nonlocal models to a brain graph called connectome. Therefore, after setting out the construction of such a graph, we move on to the description of Laplacian and convolution operations on a graph. Taking advantage of all these elements, we finally move on to the translation of the continuous models described above into discrete models on the connectome. To conclude, the results of some simulations concerning the discrete models just derived are presented.

Prognostic Value Of Dna And Mrna E6/e7 Of Human Papillomavirus In The Evolution Of Cervical Intraepithelial Neoplasia Grade 2.

This study aimed at evaluating whether human papillomavirus (HPV) groups and E6/E7 mRNA of HPV 16, 18, 31, 33, and 45 are prognostic of cervical intraepithelial neoplasia (CIN) 2 outcome in women with a cervical smear showing a low-grade squamous intraepithelial lesion (LSIL). This cohort study included women with biopsy-confirmed CIN 2 who were followed up for 12 months, with cervical smear and colposcopy performed every three months. Women with a negative or low-risk HPV status showed 100% CIN 2 regression. The CIN 2 regression rates at the 12-month follow-up were 69.4% for women with alpha-9 HPV versus 91.7% for other HPV species or HPV-negative status (P < 0.05). For women with HPV 16, the CIN 2 regression rate at the 12-month follow-up was 61.4% versus 89.5% for other HPV types or HPV-negative status (P < 0.05). The CIN 2 regression rate was 68.3% for women who tested positive for HPV E6/E7 mRNA versus 82.0% for the negative results, but this difference was not statistically significant. The expectant management for women with biopsy-confirmed CIN 2 and previous cytological tests showing LSIL exhibited a very high rate of spontaneous regression. HPV 16 is associated with a higher CIN 2 progression rate than other HPV infections. HPV E6/E7 mRNA is not a prognostic marker of the CIN 2 clinical outcome, although this analysis cannot be considered conclusive. Given the small sample size, this study could be considered a pilot for future larger studies on the role of predictive markers of CIN 2 evolution.

Identification Of Target Genes Using Gene Expression Profile Of Granulocytes From Patients With Chronic Myeloid Leukemia Treated With Tyrosine Kinase Inhibitors.

Differential gene expression analysis by suppression subtractive hybridization with correlation to the metabolic pathways involved in chronic myeloid leukemia (CML) may provide a new insight into the pathogenesis of CML. Among the overexpressed genes found in CML at diagnosis are SEPT5, RUNX1, MIER1, KPNA6 and FLT3, while PAN3, TOB1 and ITCH were decreased when compared to healthy volunteers. Some genes were identified and involved in CML for the first time, including TOB1, which showed a low expression in patients with CML during tyrosine kinase inhibitor treatment with no complete cytogenetic response. In agreement, reduced expression of TOB1 was also observed in resistant patients with CML compared to responsive patients. This might be related to the deregulation of apoptosis and the signaling pathway leading to resistance. Most of the identified genes were related to the regulation of nuclear factor κB (NF-κB), AKT, interferon and interleukin-4 (IL-4) in healthy cells. The results of this study combined with literature data show specific gene pathways that might be explored as markers to assess the evolution and prognosis of CML as well as identify new therapeutic targets.

The Crystal-t Algorithm: A New Approach To Calculate The Sle Of Lipidic Mixtures Presenting Solid Solutions.

Lipidic mixtures present a particular phase change profile highly affected by their unique crystalline structure. However, classical solid-liquid equilibrium (SLE) thermodynamic modeling approaches, which assume the solid phase to be a pure component, sometimes fail in the correct description of the phase behavior. In addition, their inability increases with the complexity of the system. To overcome some of these problems, this study describes a new procedure to depict the SLE of fatty binary mixtures presenting solid solutions, namely the Crystal-T algorithm. Considering the non-ideality of both liquid and solid phases, this algorithm is aimed at the determination of the temperature in which the first and last crystal of the mixture melts. The evaluation is focused on experimental data measured and reported in this work for systems composed of triacylglycerols and fatty alcohols. The liquidus and solidus lines of the SLE phase diagrams were described by using excess Gibbs energy based equations, and the group contribution UNIFAC model for the calculation of the activity coefficients of both liquid and solid phases. Very low deviations of theoretical and experimental data evidenced the strength of the algorithm, contributing to the enlargement of the scope of the SLE modeling.

Effects Of Therapeutic Approach On The Neonatal Evolution Of Very Low Birth Weight Infants With Patent Ductus Arteriosus.

To analyze the effects of treatment approach on the outcomes of newborns (birth weight [BW] < 1,000 g) with patent ductus arteriosus (PDA), from the Brazilian Neonatal Research Network (BNRN) on: death, bronchopulmonary dysplasia (BPD), severe intraventricular hemorrhage (IVH III/IV), retinopathy of prematurity requiring surgical (ROPsur), necrotizing enterocolitis requiring surgery (NECsur), and death/BPD. This was a multicentric, cohort study, retrospective data collection, including newborns (BW < 1000 g) with gestational age (GA) < 33 weeks and echocardiographic diagnosis of PDA, from 16 neonatal units of the BNRN from January 1, 2010 to Dec 31, 2011. Newborns who died or were transferred until the third day of life, and those with presence of congenital malformation or infection were excluded. Groups: G1 - conservative approach (without treatment), G2 - pharmacologic (indomethacin or ibuprofen), G3 - surgical ligation (independent of previous treatment). Factors analyzed: antenatal corticosteroid, cesarean section, BW, GA, 5 min. Apgar score < 4, male gender, Score for Neonatal Acute Physiology Perinatal Extension (SNAPPE II), respiratory distress syndrome (RDS), late sepsis (LS), mechanical ventilation (MV), surfactant (< 2 h of life), and time of MV. death, O2 dependence at 36 weeks (BPD36wks), IVH III/IV, ROPsur, NECsur, and death/BPD36wks. Student's t-test, chi-squared test, or Fisher's exact test; Odds ratio (95% CI); logistic binary regression and backward stepwise multiple regression. Software: MedCalc (Medical Calculator) software, version 12.1.4.0. p-values < 0.05 were considered statistically significant. 1,097 newborns were selected and 494 newborns were included: G1 - 187 (37.8%), G2 - 205 (41.5%), and G3 - 102 (20.6%). The highest mortality was observed in G1 (51.3%) and the lowest in G3 (14.7%). The highest frequencies of BPD36wks (70.6%) and ROPsur were observed in G3 (23.5%). The lowest occurrence of death/BPD36wks occurred in G2 (58.0%). Pharmacological (OR 0.29; 95% CI: 0.14-0.62) and conservative (OR 0.34; 95% CI: 0.14-0.79) treatments were protective for the outcome death/BPD36wks. The conservative approach of PDA was associated to high mortality, the surgical approach to the occurrence of BPD36wks and ROPsur, and the pharmacological treatment was protective for the outcome death/BPD36wks.

Evolution Of The Deaths Registry System In Brazil: Associations With Changes In The Mortality Profile, Under-registration Of Death Counts, And Ill-defined Causes Of Death.

This paper examines the spatial pattern of ill-defined causes of death across Brazilian regions, and its relationship with the evolution of completeness of the deaths registry and changes in the mortality age profile. We make use of the Brazilian Health Informatics Department mortality database and population censuses from 1980 to 2010. We applied demographic methods to evaluate the quality of mortality data for 137 small areas and correct for under-registration of death counts when necessary. The second part of the analysis uses linear regression models to investigate the relationship between, on the one hand, changes in death counts coverage and age profile of mortality, and on the other, changes in the reporting of ill-defined causes of death. The completeness of death counts coverage increases from about 80% in 1980-1991 to over 95% in 2000-2010 at the same time the percentage of ill-defined causes of deaths reduced about 53% in the country. The analysis suggests that the government's efforts to improve data quality are proving successful, and they will allow for a better understanding of the dynamics of health and the mortality transition.

Systemic Granulomatous Diseases Associated With Multiple Palpable Masses That May Involve The Breast: Case Presentation And An Approach To The Differential Diagnosis.

Palpable mass is a common complaint presented to the breast surgeon. It is very uncommon for patients to report breast mass associated with palpable masses in other superficial structures. When these masses are related to systemic granulomatous diseases, the diagnosis and initiation of specific therapy can be challenging. The purpose of this paper is to report a case initially assessed by the breast surgeon and ultimately diagnosed as granulomatous variant of T-cell lymphoma, and discuss the main systemic granulomatous diseases associated with palpable masses involving the breast.