Reliable Lifespan Evaluation of a Remote Environment Monitoring System Based on Wireless Sensor Networks and Global System for Mobile Communications

The use of wireless sensor networks (WSN) for monitoring physical and chemical variables in large areas allows density and frequency measurements which have been unavailable to date in classical measurement systems. To fully take advantage of this technology in a particular application, besides an accurate design and selection of all the components involved in its operation, it is essential to dispose of reliable lifetime estimation prior to deployment. This paper presents an experimental approach to determine the actual lifetime of such battery-operated systems, making use of a custom WSN architecture, and for different batteries technologies. To render a reliable evaluation, the energy consumption of the sensor nodes under their different operation modes, in correlation with the battery characteristics and the voltage regulation system, is jointly considered. The result is a complete and practical lifetime model, whose appropriate performance has been validated in a real deployment scenario

A fully-integrated 180 nm CMOS 1.2 V low-dropout regulator for low-power portable applications

This paper presents the design and postlayout simulation results of a capacitor-less low dropout (LDO) regulator fully integrated in a low-cost standard 180 nm Complementary Metal-Oxide-Semiconductor (CMOS) technology which regulates the output voltage at 1.2 V from a 3.3 to 1.3 V battery over a -40 to 120 degrees C temperature range. To meet with the constraints of system-on-chip (SoC) battery-operated devices, ultralow power (I-q = 8.6 mu A) and minimum area consumption (0.109 mm(2)) are maintained, including a reference voltage V-ref = 0.4 V. It uses a high-gain dynamically biased folded-based error amplifier topology optimized for low-voltage operation that achieves an enhanced regulation-fast transient performance trade-off

A wireless instrumentation control system based on low-cost single board computer gateways

Nowadays, most of the automatized measurement processes are carried out by VISA (Virtual Instrument Software Architecture) compatible instruments, that execute the instructions provided by a host computer connected through wired standard buses, as USB (Universal Serial Bus), GPIB (General-Purpose Instrumentation Bus), PXI (PCI eXtensions for Instrumentation) or Ethernet. To overcome the intrinsic limitations associated to these wired systems, this work presents an instrumentation control system based on the IEEE 802.11 wireless communications standard. Intended for instruments having a USB control port, this port is connected to a gateway based on a compact Raspberry Single Board Computer (SBC) and thus the instrument can be connected to the host computer via Wireless Fidelity (WiFi), easily allowing the deployment of an ad-hoc instruments communication network in the working area or its connection to a previously deployed general purpose WiFi network. Developed under Python, the operation commands, wireless link protocol, and USB connection allow two modes of operation to provide system flexibility: a live mode, where commands are sent individually from the host computer to the selected instrument; and a standalone mode, where a full measurement process can be entirely downloaded in the gateway to be autonomously executed on the instrumentation. The system performance in both operation modes, distance of operation, time latencies, and operating lifetime in battery operation have been characterized

Spontaneous Embedding of DNA Mismatches Within the RNA:DNA Hybrid of CRISPR-Cas9.

CRISPR-Cas9 is the forefront technology for editing the genome. In this system, the Cas9 protein is programmed with guide RNAs to process DNA sequences that match the guide RNA forming an RNA:DNA hybrid structure. However, the binding of DNA sequences that do not fully match the guide RNA can limit the applicability of CRISPR-Cas9 for genome editing, resulting in the so-called off-target effects. Here, molecular dynamics is used to probe the effect of DNA base pair mismatches within the RNA:DNA hybrid in CRISPR-Cas9. Molecular simulations revealed that the presence of mismatched pairs in the DNA at distal sites with respect to the Protospacer Adjacent Motif (PAM) recognition sequence induces an extended opening of the RNA:DNA hybrid, leading to novel interactions established by the unwound nucleic acids and the protein counterpart. On the contrary, mismatched pairs upstream of the RNA:DNA hybrid are rapidly incorporated within the heteroduplex, with minor effect on the protein-nucleic acid interactions. As a result, mismatched pairs at PAM distal ends interfere with the activation of the catalytic HNH domain, while mismatches fully embedded in the RNA:DNA do not affect the HNH dynamics and enable its activation to cleave the DNA. These findings provide a mechanistic understanding to the intriguing experimental evidence that PAM distal mismatches hamper a proper function of HNH, explaining also why mismatches within the heteroduplex are much more tolerated. This constitutes a step forward in understanding off-target effects in CRISPR-Cas9, which encourages novel structure-based engineering efforts aimed at preventing the onset of off-target effects

Total ozone time series analysis: a neural network model approach

International audienceThis work is focused on the application of neural network based models to the analysis of total ozone (TO) time series. Processes that affect total ozone are extremely non linear, especially at the considered European mid-latitudes. Artificial neural networks (ANNs) are intrinsically non-linear systems, hence they are expected to cope with TO series better than classical statistics do. Moreover, neural networks do not assume the stationarity of the data series so they are also able to follow time-changing situations among the implicated variables. These two features turn NNs into a promising tool to catch the interactions between atmospheric variables, and therefore to extract as much information as possible from the available data in order to make, for example, time series reconstructions or future predictions. Models based on NNs have also proved to be very suitable for the treatment of missing values within the data series. In this paper we present several models based on neural networks to fill the missing periods of data within a total ozone time series, and models able to reconstruct the data series. The results released by the ANNs have been compared with those obtained by using classical statistics methods, and better accuracy has been achieved with the non linear ANNs techniques. Different network structures and training strategies have been tested depending on the specific task to be accomplished

A Tool for Integer Homology Computation: Lambda-At Model

In this paper, we formalize the notion of lambda-AT-model (where $\lambda$ is a non-null integer) for a given chain complex, which allows the computation of homological information in the integer domain avoiding using the Smith Normal Form of the boundary matrices. We present an algorithm for computing such a model, obtaining Betti numbers, the prime numbers p involved in the invariant factors of the torsion subgroup of homology, the amount of invariant factors that are a power of p and a set of representative cycles of generators of homology mod p, for each p. Moreover, we establish the minimum valid lambda for such a construction, what cuts down the computational costs related to the torsion subgroup. The tools described here are useful to determine topological information of nD structured objects such as simplicial, cubical or simploidal complexes and are applicable to extract such an information from digital pictures.Comment: Journal Image and Vision Computing, Volume 27 Issue 7, June, 200

Equatorial ozone characteristics as measured at Natal (5.9 deg S, 35.2 deg W)

Ozone density profiles obtained through electrochemical concentration cell (ECC) sonde measurements at Natal were analyzed. Time variations, as expected, are small. Outstanding features of the data are tropospheric densities substantially higher than those measured at other stations, and also a total ozone content that is higher than the averages given by satellite measurements

Voltage-to-Frequency Converter for Low-Power Sensor Interfaces

This work presents a low-power rail-to-rail temperature compensated voltage-to-frequency converter (VFC) which constitutes the last stage of a sensor read-out interface targeting wireless sensor networks (WSN) applications. These quasi-digital converters are now receiving great interest, since they combine the simplicity of analog devices with the accuracy and noise immunity proper to digital signal processing; besides, frequency output is directly driven to the embedded node microcontroller C, which next performs the A/D conversion using its internal timers. A first read-out interface prototype using low-voltage low-power commercial components shows that the VFC means 99 % of the total interface consumption in read-out mode. Further, existing CMOS VFCs in the form of ASICs have a rather limited input range and an unsuitable output frequency span for typical C clock frequencies used in WSN. Hence, a novel full custom VFC solution is needed, fullfilling the main requirements of rail-to-rail operation, to take advantage of the full supply voltage range to optimize the output frequency resolution, and low-power low-voltage operation to have a power supply compatible with conventional WSN batteries while maximizing the operating life of the sensor node. Experimental results for a 0.18–μm 1.2–V CMOS VFC implementation show for an input range of (0–1.2 V) an output frequency range of (0.1–1.0 MHz), adequate to digitize the signal with the direct counting method in the sensor node μC achieving 13 bits resolution. It has a power consumption of 60 μW (35 nW in sleep mode) and it is temperature insensitive for a temperature range of (-40, 120 ºC)