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

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

Low-power 3V single supply lock-in amplifier

In extreme high noise level environments, linear filtering is not a suitable processing method and special techniques for accurately extracting sensor signal information should be considered. An interesting possibility are lock-in amplifiers (LIA), which use the phase sensitive detection technique (PSD) to take out the data signal at a specific reference frequency fo while noise signals at frequencies other than fo are rejected and do not affect significantly the measurement. Current commercial LIAs are expensive, heavy and power consuming devices, which preclude their use in portable sensing systems. Thus, this work analyses the possibility of exporting this technique to low-power low-voltage (LPLV) embedded applications. In particular, the aim is to implement a signal conditioning lock-in architecture suitable for 3V single battery-operated wireless sensor nodes. This implies to re-design all the processing elements in single supply -most reported LIAs are designed using dual power supply- and compatible with the power requirements of a wireless sensor network node. Further, looking for a compact LPLV solution, instead of a traditional sinusoidal input, a square wave input is considered, which can be directly obtained from the embedded microcontroller, thus avoiding blocks like a sinusoidal oscillator or function generator. Figure 1 shows the proposed block diagram and a photograph of the implemented device. Experimental results for signals buried in white noise, flicker noise, interference contamination and common-mode voltage contamination confirm the capability of the proposed solution to recover information from signal to noise ratios down to 24 dB with errors below 6% with an average power consumption of only 5 mW in full operation, being able to process signals with frequencies up to 43 kHz, as shown in Figure 2

A 1.8 v Gm-C Highly Tunable Low Pass Filter for Sensing Applications

This paper presents a fully integrated, first-order Low Pass Filter with 2-tuning points giving a wide versatility to the filter. It allows for a fine/thick tuning with a cutoff frequency that spans over several orders of magnitude, from 220 mHz to 39.1 kHz. The Gm-C filter proposed is designed in a 180 nm CMOS technology with a total power consumption of 1.08 µW for a 1.8 V power supply and a dynamic range up to 73 dB. The proposed filter is a very competitive solution compared with previously reported works, meeting the requirements for portable on chip sensor interfaces based on impedance spectroscopy and biosignal front-end interfaces

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

Wide-band compact 1.8 V-0.18 µm CMOS analog front-end for impedance spectroscopy

In this letter, a fully integrated configurable front-end for Impedance Spectroscopy (IS) is presented. The circuit includes fully differential in-phase and quadrature channels, using a transconductor (TC)-transimpedance (TI) approach. The input TC, shared for both channels, is based on a programmable degenerated differential pair to attain low-noise programmable-gain, while identical TII/Q with embedded synchronous rectification provide both I, Q outputs, filtered through fc adjustable Gm-C integrators. It exhibits a programmable gain ranging from 0 dB to 40 dB with 87 MHz bandwidth, amplitude and phase recovery errors below 1.9% and 2.5∘ respectively and an input referred noise floor of 16.7 nV/Hz. The result is a high-performance very compact topology with a total power consumption of 292 μW at a 1.8 V power supply, thus constituting an appropriate solution for full on chip multichannel IS systems

A CMOS self-contained quadrature signal generator for soc impedance spectroscopy

This paper presents a low-power fully integrated quadrature signal generator for system-on-chip (SoC) impedance spectroscopy applications. It has been designed in a 0.18 µm-1.8 V CMOS technology as a self-contained oscillator, without the need for an external reference clock. The frequency can be digitally tuned from 10 to 345 kHz with 12-bit accuracy and a relative mean error below 1.7%, thus supporting a wide range of impedance sensing applications. The proposal is experimentally validated in two impedance spectrometry examples, achieving good magnitude and phase recovery results compared to the results obtained using a commercial LCR-meter. Besides the wide frequency tuning range, the proposed programmable oscillator features a total power consumption lower than 0.77 mW and an active area of 0.129 mm2, thus constituting a highly suitable choice as stimulation module for instrument-on-a-chip devices

Semiclassical and Quantum Black Holes and their Evaporation, de Sitter and Anti-de Sitter Regimes, Gravitational and String Phase Transitions

An effective string theory in physically relevant cosmological and black hole space times is reviewed. Explicit computations of the quantum string entropy, partition function and quantum string emission by black holes (Schwarzschild, rotating, charged, asymptotically flat, de Sitter dS and AdS space times) in the framework of effective string theory in curved backgrounds provide an amount of new quantum gravity results as: (i) gravitational phase transitions appear with a distinctive universal feature: a square root branch point singularity in any space time dimensions. This is of the type of the de Vega - Sanchez transition for the thermal self-gravitating gas of point particles. (ii) There are no phase transitions in AdS alone. (iii) For $dS$ background, upper bounds of the Hubble constant H are found, dictated by the quantum string phase transition.(iv) The Hawking temperature and the Hagedorn temperature are the same concept but in different (semiclassical and quantum) gravity regimes respectively. (v) The last stage of black hole evaporation is a microscopic string state with a finite string critical temperature which decays as usual quantum strings do in non-thermal pure quantum radiation (no information loss).(vi) New lower string bounds are given for the Kerr-Newman black hole angular momentum and charge, which are entirely different from the upper classical bounds. (vii) Semiclassical gravity states undergo a phase transition into quantum string states of the same system, these states are duals of each other in the precise sense of the usual classical-quantum (wave-particle) duality, which is universal irrespective of any symmetry or isommetry of the space-time and of the number or the kind of space-time dimensions.Comment: review paper, no figures. to appear in Int Jour Mod Phys

Protein interaction perturbation profiling at amino-acid resolution

The identification of genomic variants in healthy and diseased individuals continues to rapidly outpace our ability to functionally annotate these variants. Techniques that both systematically assay the functional consequences of nucleotide-resolution variation and can scale to hundreds of genes are urgently required. We designed a sensitive yeast two-hybrid-based 'off switch' for positive selection of interaction-disruptive variants from complex genetic libraries. Combined with massively parallel programmed mutagenesis and a sequencing readout, this method enables systematic profiling of protein-interaction determinants at amino-acid resolution. We defined >1,000 interaction-disrupting amino acid mutations across eight subunits of the BBSome, the major human cilia protein complex associated with the pleiotropic genetic disorder Bardet–Biedl syndrome. These high-resolution interaction-perturbation profiles provide a framework for interpreting patient-derived mutations across the entire protein complex and thus highlight how the impact of disease variation on interactome networks can be systematically assessed