Evaluation of modern and mid-Holocene seasonal precipitation of the Mediterranean and northern Africa in the CMIP5 simulations

We analyse the spatial expression of seasonal climates of the Mediterranean and northern Africa in pre-industrial (piControl) and mid-Holocene (midHolocene, 6 yr BP) simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Modern observations show four distinct precipitation regimes characterized by differences in the seasonal distribution and total amount of precipitation: an equatorial band characterized by a double peak in rainfall, the monsoon zone characterized by summer rainfall, the desert characterized by low seasonality and total precipitation, and the Mediterranean zone characterized by summer drought. Most models correctly simulate the position of the Mediterranean and the equatorial climates in the piControl simulations, but overestimate the extent of monsoon influence and underestimate the extent of desert. However, most models fail to reproduce the amount of precipitation in each zone. Model biases in the simulated magnitude of precipitation are unrelated to whether the models reproduce the correct spatial patterns of each regime. In the midHolocene, the models simulate a reduction in winter rainfall in the equatorial zone, and a northward expansion of the monsoon with a significant increase in summer and autumn rainfall. Precipitation is slightly increased in the desert, mainly in summer and autumn, with northward expansion of the monsoon. Changes in the Mediterranean are small, although there is an increase in spring precipitation consistent with palaeo-observations of increased growing-season rainfall. Comparison with reconstructions shows most models underestimate the mid-Holocene changes in annual precipitation, except in the equatorial zone. Biases in the piControl have only a limited influence on midHolocene anomalies in ocean–atmosphere models; carbon-cycle models show no relationship between piControl bias and midHolocene anomalies. Biases in the prediction of the midHolocene monsoon expansion are unrelated to how well the models simulate changes in Mediterranean climate

Masseter muscle thickness measured by ultrasound as a possible link with sarcopenia, malnutrition and dependence in nursing homes

Sarcopenia is a progressive and generalized loss of skeletal muscle mass and strength. It is frequently associated with malnutrition and dependence in nursing homes. Masticatory muscle strength could be the link between sarcopenia, malnutrition and dependence. We aimed to study the relation between sarcopenia, malnutrition and dependence with masseter muscle thickness measured by ultrasound. A cross-sectional study was realized, with 464 patients from 3 public nursing homes in Zaragoza (Spain). The diagnosis of sarcopenia was assessed according to the EuropeanWorking Group on Sarcopenia in Older People 2 criteria, malnutrition by the Mini Nutritional Assessment (MNA) and the Global Leadership Initiative on Malnutrition (GLIM) criteria and functional capacity by the Barhel Index and the texture diet. Masseter muscle thickness (MMT) was measured by ultrasound. The median age was 84.7 years, and 70% of the participants were women. Sarcopenia was confirmed in 39.2% of patients, malnutrition in 26.5% (risk 47.8%), total dependence in 37.9% and diet texture was modified in 44.6%. By logistic regression, once the model was adjusted for age, sex, Barthel index and texture diet, our analyses indicated that each 1 mm decrease in MMT increased the risk of sarcopenia by ~57% (OR: 0.43), the risk of malnutrition by MNA by ~63% (OR: 0.37) and the risk of malnutrition by GLIM by ~34% (OR: 0.66). We found that MMT was reduced in sarcopenic, malnourished and dependent patients, and it could be the common point of a vicious cycle between sarcopenia and malnutrition. Further studies are needed to establish causality. © 2021 by the authors

Single-molecule electrical contacts on silicon electrodes under ambient conditions

The ultimate goal in molecular electronics is to use individual molecules as the active electronic component of a real-world sturdy device. For this concept to become reality, it will require the field of single-molecule electronics to shift towards the semiconducting platform of the current microelectronics industry. Here, we report silicon-based single-molecule contacts that are mechanically and electrically stable under ambient conditions. The single-molecule contacts are prepared on silicon electrodes using the scanning tunnelling microscopy break-junction approach using a top metallic probe. The molecular wires show remarkable current–voltage reproducibility, as compared to an open silicon/nano-gap/metal junction, with current rectification ratios exceeding 4,000 when a low-doped silicon is used. The extension of the single-molecule junction approach to a silicon substrate contributes to the next level of miniaturization of electronic components and it is anticipated it will pave the way to a new class of robust single-molecule circuits

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

Visible and near-infrared observations of asteroid 2012 DA14 during its closest approach of February 15, 2013

Near-Earth asteroid 2012 DA14 made its closest approach on February 15, 2013, when it passed at a distance of 27,700 km from the Earth's surface. It was the first time an asteroid of moderate size was predicted to approach that close to the Earth, becoming bright enough to permit a detailed study from ground-based telescopes. Asteroid 2012 DA14 was poorly characterized before its closest approach. We acquired data using several telescopes on four Spanish observatories: the 10.4m Gran Telescopio Canarias (GTC) and the 3.6m Telescopio Nazionale Galileo (TNG), both in the El Roque de los Muchachos Observatory (ORM, La Palma); the 2.2m CAHA telescope, in the Calar Alto Observatory (Almeria); the f/3 0.77m telescope in the La Hita Observatory (Toledo); and the f/8 1.5m telescope in the Sierra Nevada Observatory (OSN, Granada). We obtained visible and near-infrared color photometry, visible spectra and time-series photometry. Visible spectra together with color photometry of 2012 DA14 show that it can be classified as an L-type asteroid, a rare spectral type with a composition similar to that of carbonaceous chondrites. The time-series photometry provides a rotational period of 8.95 +- 0.08 hours after the closest approach, and there are indications that the object suffered a spin-up during this event. The large amplitude of the light curve suggests that the object is very elongated and irregular, with an equivalent diameter of around 18m. We obtain an absolute magnitude of H_R = 24.5 +- 0.2, corresponding to H_V = 25.0 +- 0.2. The GTC photometry also gives H_V = 25.29 +- 0.14. Both values agree with the value listed at the Minor Planet Center shortly after discovery. From the absolute photometry, together with some constraints on size and shape, we compute a geometric albedo of p_V = 0.44 +- 0.20, which is slightly above the range of albedos known for L-type asteroids (0.082 - 0.405).Comment: 7 pages, 4 figures, 1 table. Accepted in A&A (June 17 2013

A dandelion-encoded evolutionary algorithm for the delay-constrained capacitated minimum spanning tree problem

This paper proposes an evolutionary algorithm with Dandelion-encoding to tackle the Delay-Constrained Capacitated Minimum Spanning Tree (DC-CMST) problem. This problem has been recently proposed, and consists of finding several broadcast trees from a source node, jointly considering traffic and delay constraints in trees. A version of the problem in which the source node is also included in the optimization process is considered as well in the paper. The Dandelion code used in the proposed evolutionary algorithm has been recently proposed as an effective way of encoding trees in evolutionary algorithms. Good properties of locality has been reported on this encoding, which makes it very effective to solve problems in which the solutions can be expressed in form of trees. In the paper we describe the main characteristics of the algorithm, the implementation of the Dandelion-encoding to tackled the DC-CMST problem and a modification needed to include the source node in the optimization. In the experimental section of this article we compare the results obtained by our evolutionary with that of a recently proposed heuristic for the DC-CMST. the Least Cost (LC) algorithm. We show that our Dandelion-encoded evolutionary algorithm is able to obtain better results that the LC in all the instances tackled. (C) 2008 Elsevier B.V. All rights reserved

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

Neck circumference is associated with nutritional status in elderly nursing home residents

Objectives: Anthropometry is an easy and noninvasive method to evaluate nutritional status in institutionalized elderly people who are often bedridden. The aim of this study was to investigate the relationship between the neck circumference (NC) and nutritional status of elderly nursing home residents and to find cutoff points for NC size to identify individuals at risk of malnutrition. Methods: A cross-sectional study was developed with data collected from 352 elderly people living in five public nursing homes. Different anthropometric measures and the Mini Nutritional Assessment (MNA) were used to determine nutritional status. Receiver operating characteristic (ROC) curves were built for each anthropometric variable to determine their sensitivity and specificity for predicting the risk of malnutrition according to the MNA. Results: The mean age of the participants (59% females) was 83 years old. In total, 48.3% of women and 45.5% of men were at risk of malnutrition according to their MNA scores. All anthropometric measurements were highly intercorrelated in both men and women, indicating a high degree of collinearity. Bootstrapped linear regression was used to assess the strength of the association between an individuals’ nutritional status and their anthropometric parameters. Calf circumference and NC presented the best predictive value with the highest sensitivity for diagnosing the risk of malnutrition in both institutionalized elderly men and women. The best cutoff points of NC to identify elderly nursing home residents at risk of malnutrition were 35.2 cm for females and 37.8 cm for males. Conclusions: NC is associated with other classical anthropometric parameters and malnutrition status in elderly people living in nursing homes

Artificial Neural Network to predict mean monthly total ozone in Arosa, Switzerland

Present study deals with the mean monthly total ozone time series over Arosa, Switzerland. The study period is 1932-1971. First of all, the total ozone time series has been identified as a complex system and then Artificial Neural Networks models in the form of Multilayer Perceptron with back propagation learning have been developed. The models are Single-hidden-layer and Two-hidden-layer Perceptrons with sigmoid activation function. After sequential learning with learning rate 0.9 the peak total ozone period (February-May) concentrations of mean monthly total ozone have been predicted by the two neural net models. After training and validation, both of the models are found skillful. But, Two-hidden-layer Perceptron is found to be more adroit in predicting the mean monthly total ozone concentrations over the aforesaid period.Comment: 22 pages, 14 figure