Analysis of inorganic anions in drainage water and soil solution by single-column ion chromatography

Single-column ion chromatography (SCIC) for anion determination in drainage water and soil solution was tested. The SCIC minimum detection limits (100-microliter sample loop) were 0.75 mg l-1 for Cl-, 0.2 mg l-1 for NO2-N, 0.02 mg l-1 for NO3-N, 1.25 mg l-1 for HPO4-P, and 0.5 mg l-1 for SO4-S. The results showed a high reproducibility. Results for Cl-, NO3-N and SO4-S obtained by the SCIC method were compared with those obtained by traditional methods; Student's t-test and regression analysis showed that the methods agree closely.     

In vivo phosphorylation of phosphofructokinase from the bivalve mollusk Mytilus galloprovincialis

The objective of this study was to determine whether progesterone prevents the stimulatory effects of oestradiol on GnRH receptor gene expression. In Expt 1, ewes were treated during the luteal phase (days 10-12 of the oestrous cycle) with either one or five subcutaneous implants containing oestradiol (n = 6 per group). Control ewes received no treatment (n = 6). Anterior pituitary glands were collected 16 h after treatment with oestradiol. Steady-state amounts of GnRH receptor mRNA were similar among all three treatment groups despite increased circulating concentrations of oestradiol in implanted ewes at the time of pituitary collection (4.3 +/- 0.6 and 24.7 +/- 2.6 pg ml-1 in ewes treated with one or five implants, respectively, compared with 0.5 pg ml-1 in controls). Experiment 2 was designed to determine whether progesterone was the ovarian factor preventing the stimulatory effects of oestradiol on expression of the GnRH receptor gene in Expt 1. Twenty-five ewes were ovariectomized on day 6 or day 7 of the oestrous cycle and assigned to one of five treatment groups (n = 5 per group). Control ewes received no further treatment. Endogenous luteal phase concentrations of progesterone were replaced in three groups of ewes at the time of ovariectomy via intravaginal implants. Three days after ovariectomy, one group of progesterone-treated ewes received one oestradiol implant, while another group of progesterone-treated ewes received five oestradiol implants. An additional group was treated with five oestradiol implants only, and anterior pituitary glands were collected from all ewes 16 h later. Compared with untreated ovariectomized ewes, treatment with progesterone alone did not affect amounts of GnRH receptor mRNA. In ewes treated with progesterone and either one or five oestradiol implants, steady-state amounts of GnRH receptor mRNA were increased twofold (P < 0.01). Treatment with oestradiol in the absence of progesterone increased amounts of GnRH receptor mRNA threefold (P < 0.001). These results provide evidence that the stimulatory effects of oestradiol on the expression of the GnRH receptor gene are prevented during the natural luteal phase in ewes. However, progesterone does not appear to act independently to mediate this effect.     

A Timing Assumption and Two t-Resilient Protocols for Implementing an Eventual Leader Service in Asynchronous Shared Memory Systems

This paper considers the problem of electing an eventual leader in an asynchronous shared memory system. While this problem has received a lot of attention in message-passing systems, very few solutions have been proposed for shared memory systems. As an eventual leader cannot be elected in a pure asynchronous system prone to process crashes, the paper first proposes to enrich the asynchronous system model with an additional assumption. That assumption (denoted AWB) is particularly weak. It is made up of two complementary parts. More precisely, it requires that, after some time, (1) there is a process whose write accesses to some shared variables be timely, and (2) the timers of (t−f) other processes be asymptotically well-behaved (t denotes the maximal number of processes that may crash, and f the actual number of process crashes in a run). The asymptotically well-behaved timer notion is a new notion that generalizes and weakens the traditional notion of timers whose durations are required to monotonically increase when the values they are set to increase (a timer works incorrectly when it expires at arbitrary times, i.e., independently of the value it has been set to). The paper then focuses on the design of t-resilient AWB-based eventual leader protocols. “t-resilient” means that each protocol can cope with up to t process crashes (taking t=n−1 provides wait-free protocols, i.e., protocols that can cope with any number of process failures). Two protocols are presented. The first enjoys the following noteworthy properties: after some time only the elected leader has to write the shared memory, and all but one shared variables have a bounded domain, be the execution finite or infinite. This protocol is consequently optimal with respect to the number of processes that have to write the shared memory. The second protocol guarantees that all the shared variables have a bounded domain. This is obtained at the following additional price: t+1 processes are required to forever write the shared memory. A theorem is proved which states that this price has to be paid by any protocol that elects an eventual leader in a bounded shared memory model. This second protocol is consequently optimal with respect to the number of processes that have to write in such a constrained memory model. In a very interesting way, these protocols show an inherent tradeoff relating the number of processes that have to write the shared memory and the bounded/unbounded attribute of that memory.     

Automatic bearing fault diagnosis based on one-class ν-SVM

Rolling-element bearings are among the most used elements in industrial machinery, thus an early detection of a defect in these components is necessary to avoid major machine failures. Vibration analysis is a widely used condition monitoring technique for high-speed rotating machinery. Using the information contained in the vibration signals, an automatic method for bearing fault detection and diagnosis is presented in this work. Initially, a one-class ν-SVM is used to discriminate between normal and faulty conditions. In order to build a model of normal operation regime, only data extracted under normal conditions is used. Band-pass filters and Hilbert Transform are then used sequentially to obtain the envelope spectrum of the original raw signal that will finally be used to identify the location of the problem. In order to check the performance of the method, two different data sets are used: (a) real data from a laboratory test-to-failure experiment and (b) data obtained from a fault-seeded bearing test. The results showed that the method was able not only to detect the failure in an incipient stage but also to identify the location of the defect and qualitatively assess its evolution over time.     

Control of attendance applied in higher education through mobile NFC technologies

This paper presents an improved attendance control system, required for continuous evaluation which has become compulsory following the Bologna Process. It provides a solution based on NFC technology and is based on a real project developed and pilot tested at the “Universidad Pontificia de Salamanca, Campus Madrid”.     

Classification of signals by means of Genetic Programming

This paper describes a new technique for signal classification by means of Genetic Programming (GP). The novelty of this technique is that no prior knowledge of the signals is needed to extract the features. Instead of it, GP is able to extract the most relevant features needed for classification. This technique has been applied for the solution of a well-known problem: the classification of EEG signals in epileptic and healthy patients. In this problem, signals obtained from EEG recordings must be correctly classified into their corresponding class. The aim is to show that the technique described here, with the automatic extraction of features, can return better results than the classical techniques based on manual extraction of features. For this purpose, a final comparison between the results obtained with this technique and other results found in the literature with the same database can be found. This comparison shows how this technique can improve the ones found.     

A parallel evolutionary algorithm for technical market indicators optimization

This paper deals with the optimization of parameters of technical indicators for stock market investment. Price prediction is a problem of great complexity and, usually, some technical indicators are used to predict market trends. The main difficulty in using technical indicators lies in deciding a set of parameter values. We proposed the use of Multi-Objective Evolutionary Algorithms (MOEAs) to obtain the best parameter values belonging to a collection of indicators that will help in the buying and selling of shares. The experimental results indicate that our MOEA offers a solution to the problem by obtaining results that improve those obtained through technical indicators with standard parameters. In order to reduce execution time is necessary to parallelize the executions. Parallelization results show that distributing the workload of indicators in multiple processors to improve performance is recommended. This parallelization has been performed taking advantage of the idle time in a corporate technology infrastructure. We have configured a small parallel grid using the students Labs of a Computer Science University College.     

Modelling opinion formation driven communities in social networks

In a previous paper we proposed a model to study the dynamics of opinion formation in human societies by a co-evolution process involving two distinct time scales of fast transaction and slower network evolution dynamics. In the transaction dynamics we take into account short range interactions as discussions between individuals and long range interactions to describe the attitude to the overall mood of society. The latter is handled by a uniformly distributed parameter α, assigned randomly to each individual, as quenched personal bias. The network evolution dynamics is realised by rewiring the societal network due to state variable changes as a result of transaction dynamics. The main consequence of this complex dynamics is that communities emerge in the social network for a range of values in the ratio between time scales. In this paper we focus our attention on the attitude parameter α and its influence on the conformation of opinion and the size of the resulting communities. We present numerical studies and extract interesting features of the model that can be interpreted in terms of social behaviour.     

A low power voltage limiter for a full passive UHF RFID sensor on a 0.35 μm CMOS process

This paper presents a low power voltage limiter design for avoiding possible damages in the analog front-end of a RFID sensor due to voltage surges whenever readers and tags are close. The proposed voltage limiter design takes advantage of the implemented bandgap reference and voltage regulator blocks in order to provide low deviation of the limiting voltage due to temperature variation and process dispersion. The measured limiting voltage is 2.9 V with a voltage deviation of only ±0.065 V for the 12 measured dies. The measured current consumption is only 150 nA when the reader and the tag are far away, not limiting the sensitivity of the tag due to an undesired consumption in the voltage limiter. The circuit is implemented on a low cost 2P4M 0.35 μm CMOS technology.     

Energy storage in symmetric and asymmetric supercapacitors based in carbon cloth/polyaniline–carbon black nanocomposites

In this work, the construction of electrochemical capacitors using polyaniline–carbon black nanocomposites as electrode material is described. Symmetric and asymmetric cells were assembled. The active material was supported on carbon cloth acting as current collector as well. The electrolyte was H₂SO₄ 0.5 M, and the selected potential range was 1 V. The electrochemical behavior of the arrayed supercapacitors was studied by cyclic voltammetry and galvanostatic charge/discharge runs. At a constant current density of 0.3 A/g, a specific capacitance value of 1039 F/g was obtained for a symmetric assembly using both electrodes prepared with polyaniline and carbon black nanocomposites. When the set is asymmetric, being the positive electrode made of polyaniline and carbon black nanocomposites, the specific capacitance value is 1534 F/g. For the latter array, the specific power and energy density values are 300 W/kg and 426 Wh/kg at 0.3 A/g, and 13 700 W/kg and 28 Wh/kg at 13.7 A/g. These results suggest a good capacity of fast energy transfer. Moreover, this asymmetric supercapacitor demonstrated a high stability over 1000 cycles being the loss of only 5%. Copyright © 2015 John Wiley & Sons, Ltd.