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

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

Determination of lactadherin concentration in dairy by-products by ELISA: Effect of heat treatment and hydrolysis

Lactadherin is a peripheral glycoprotein of the milk fat globule membrane with several attributed biological activities. In this study, we developed an indirect competitive ELISA to determine lactadherin concentration by using a rabbit polyclonal antiserum. The ELISA was applied to quantify lactadherin in several dairy by-products. Of the products tested, raw and commercial buttermilk had the highest concentrations of lactadherin (6.79 and 5.27 mg/g of product, respectively), followed by commercial butter serum (4.86 mg/g), commercial skim milk (4.84 mg/g), and raw whey (1.20 mg/g). The concentration of immunoreactive lactadherin was also determined in dairy by- products after they were subjected to different technological treatments. Thus, raw products were heat treated at combinations of temperature and time typically used in the dairy industry, and commercial products were hydrolyzed using 3 proteolytic enzyme preparations. Heat treatments of whey and buttermilk resulted in a smaller decrease in lactadherin concentration than did hydrolysis as determined by ELISA and electrophoresis. At high temperatures for long durations, the loss of lactadherin was higher in whey than in buttermilk, with the maximal reduction of around 48% found after treating whey at 72 degrees C for 60 min. Hydrolysis of commercial products with proteolytic enzymes resulted in a marked decrease of immunoreactivity within the first 5 min of treatment, which thereafter was constant throughout 4 h of hydrolysis. These results demonstrate that dairy by- products from milk fat processing are good natural sources of lactadherin, although technological processes have to be considered, because they have different effects on lactadherin content

NIKEL: Electronics and data acquisition for kilopixels kinetic inductance camera

A prototype of digital frequency multiplexing electronics allowing the real time monitoring of microwave kinetic inductance detector (MKIDs) arrays for mm-wave astronomy has been developed. Thanks to the frequency multiplexing, it can monitor simultaneously 400 pixels over a 500 MHz bandwidth and requires only two coaxial cables for instrumenting such a large array. The chosen solution and the performances achieved are presented in this paper.Comment: 21 pages, 14 figure

Bi-layer Kinetic Inductance Detectors for space observations between 80-120 GHz

We have developed Lumped Element Kinetic Inductance Detectors (LEKID) sensitive in the frequency band from 80 to 120~GHz. In this work, we take advantage of the so-called proximity effect to reduce the superconducting gap of Aluminium, otherwise strongly suppressing the LEKID response for frequencies smaller than 100~GHz. We have designed, produced and optically tested various fully multiplexed arrays based on multi-layers combinations of Aluminium (Al) and Titanium (Ti). Their sensitivities have been measured using a dedicated closed-circle 100 mK dilution cryostat and a sky simulator allowing to reproduce realistic observation conditions. The spectral response has been characterised with a Martin-Puplett interferometer up to THz frequencies, and with a resolution of 3~GHz. We demonstrate that Ti-Al LEKID can reach an optical sensitivity of about $1.4$ $10^{-17}$~$W/Hz^{0.5}$ (best pixel), or $2.2$ $10^{-17}$~$W/Hz^{0.5}$ when averaged over the whole array. The optical background was set to roughly 0.4~pW per pixel, typical for future space observatories in this particular band. The performance is close to a sensitivity of twice the CMB photon noise limit at 100~GHz which drove the design of the Planck HFI instrument. This figure remains the baseline for the next generation of millimetre-wave space satellites.Comment: 7 pages, 9 figures, submitted to A&

Q fever mimicking herpetic encephalitis

We describe a patient with temporal lobe encephalitis associated with primary Coxiella burnetii infection who lsresented with CT and MRI findings suggestive of herpes simplex encephaktis and an initial improvement during treatment with acyclovir. Q fever should be considered in the differential diagnosis of patients whose manifestations suggest herpes encephalitis

A Fully-Integrated CMOS LDO Regulator for Battery-Operated On-Chip Measurement Systems

This paper presents a fully-integrated 0.18 mu m CMOS low drop-out (LDO) regulator designed to drive on-chip low power frontend sensor nodes. The proposed LDO is based on a simple telescopic amplifier stage with internal cascode compensation driving a PMOS pass-device, providing a high precision 1.8 V output voltage for input voltages from 3.6 V to 1.92 V up to a 50 mA load current with only 22 mu A quiescent current. Line and load regulation are respectively better than 0.017 mV/V and 0.003 mV/mA, while recovery times are below 4 mu s over a (-40 degrees C, 120 degrees C) temperature span

A Conceptual Model for Planning and Management of Areas of Public Space and Meeting in Colombia

A refined investigation of new trends in urban analysis assuming a sustainable design of Areas of Public Space and Meeting (APSM) is a fundamental response to the challenges of inclusive and efficient cities. Even though the APSM are districts regarded as urban structuring systems, there is a lack of territorial planning instruments and conceptual models aimed at explaining their long-term dynamics. Based on these premises, we developed a conceptual model that articulates relevant variables of interest for the planning and management of APSM. The construction of the model includes the review and analysis of the literature and the validation process based on a consultation with a panel of experts on the subject. Our findings demonstrate that the existing research does not address the APSM issue adequately, and the methodologies proposed so far do not lead to accurate and comprehensive analyses of urban complexity in light of sustainability targets. There are only isolated, disjointed, and partial approaches to variables of interest, making it difficult to carry out holistic studies. Our technical and scientific proposal offers a framework for an exhaustive evaluation of these areas. The model has been structured according to the assumptions of urban sustainability and can be applied to diverse urban environments in South America

A CMOS Mixed Mode Non-Linear Processing Unit for Adaptive Sensor Conditioning in Portable Smart Systems

This paper presents the architecture of a novel non-linear digitally programmable analog unit for sensor output conditioning in battery-operated smart systems. Designed in an 180nm 1.8V standard CMOS technology, by properly setting the 6-bit registers in the arithmetic unit, the voltage inputs are weighted before being processed by a non-linear circuit. Thus, a processing system consisting of a set of these devices suitably tuned and interconnected can be applied to condition a non-linear sensor, improving its behavior both in linearity and operating range, while reducing the effects of cross sensitivity. The robustness of the digital weight tuning is tested simulating a chip-on-the-loop training using a Levenberg-Marquardt-based algorithm. Electric simulations of the proposed unit and the results of its application in a complete neural network-based processing system to improve the linear operating range of a thermistor are presented

Kurcuma: a kitchen utensil recognition collection for unsupervised domain adaptation

The use of deep learning makes it possible to achieve extraordinary results in all kinds of tasks related to computer vision. However, this performance is strongly related to the availability of training data and its relationship with the distribution in the eventual application scenario. This question is of vital importance in areas such as robotics, where the targeted environment data are barely available in advance. In this context, domain adaptation (DA) techniques are especially important to building models that deal with new data for which the corresponding label is not available. To promote further research in DA techniques applied to robotics, this work presents Kurcuma (Kitchen Utensil Recognition Collection for Unsupervised doMain Adaptation), an assortment of seven datasets for the classification of kitchen utensils—a task of relevance in home-assistance robotics and a suitable showcase for DA. Along with the data, we provide a broad description of the main characteristics of the dataset, as well as a baseline using the well-known domain-adversarial training of neural networks approach. The results show the challenge posed by DA on these types of tasks, pointing to the need for new approaches in future work.Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This work was supported by the I+D+i project TED2021-132103A-I00 (DOREMI), funded by MCIN/AEI/10.13039/501100011033. Some of the computing resources were provided by the Generalitat Valenciana and the European Union through the FEDER funding program (IDIFEDER/2020/003). The second author is supported by grant APOSTD/2020/256 from “Programa I+D+i de la Generalitat Valenciana”