メキシコの半乾燥地における異なる有機物の施用効果

In semiarid areas of Mexico, lack of organic matter is a major constraint for production of corn and frijol beans, the main crops of the region. A multi-year experiment was carried out at the CENGUA Experiment Station, Guanajuato State, Mexico. Soil moisture was highest in the treatments with 100% or 67% of corn residues. Yields of frijol beans increased as the proportion of corn residues increased in all three years, but there was no significant difference between the treatment with all corn residues and the treatment with one-third reduction of corn residues in two of the three years. The harvest index was highest in the same two treatments with higher proportions of corn residues in the last years. These results suggest that corn residues can be reduced by one third in fertilization of corn-frijol bean systems while maintaining adequate frijol bean yields. This could assist in establishment of sustainable corn-frijol bean-cattle integrated agriculture in semi-arid areas of Mexico

A 1024-Channel 10-Bit 36-μW/ch CMOS ROIC for Multiplexed GFET-Only Sensor Arrays in Brain Mapping

This paper presents a 1024-channel neural read-out integrated circuit (ROIC) for solution-gated GFET sensing probes in massive muECoG brain mapping. The proposed time-domain multiplexing of GFET-only arrays enables low-cost and scalable hybrid headstages. Low-power CMOS circuits are presented for the GFET analog frontend, including a CDS mechanism to improve preamplifier noise figures and 10-bit 10-kS/s A/D conversion. The 1024-channel ROIC has been fabricated in a standard 1.8-V 0.18-mum CMOS technology with 0.012 mm 2 and 36 mu W per channel. An automated methodology for the in-situ calibration of each GFET sensor is also proposed. Experimental ROIC tests are reported using a custom FPGA-based muECoG headstage with 16times 32 and 32times 32 GFET probes in saline solution and agar substrate. Compared to state-of-art neural ROICs, this work achieves the largest scalability in hybrid platforms and it allows the recording of infra-slow neural signals

Multiplexed neural sensor array of graphene solution-gated field-effect transistors

Altres ajuts: this work has made use of the Spanish ICTS Network MICRONANOFABS partially supported by MICINN and the ICTS 'NANBIOSIS', more specifically by the Micro-NanoTechnology Unit of the CIBER in Bioengineering, Biomaterials and Nanomedicine (CIBERBBN) at the IMB-CNM.Electrocorticography (ECoG) is a well-established technique to monitor electrophysiological activity from the surface of the brain and has proved crucial for the current generation of neural prostheses and brain-computer interfaces. However, existing ECoG technologies still fail to provide the resolution necessary to accurately map highly localized activity across large brain areas, due to the rapidly increasing size of connector footprint with sensor count. This work demonstrates the use of a flexible array of graphene solution-gated field-effect transistors (gSGFET), exploring the concept of multiplexed readout using an external switching matrix. This approach does not only allow for an increased sensor count, but due to the use of active sensing devices (i.e. transistors) over microelectrodes it makes additional buffer transistors redundant, which drastically eases the complexity of device fabrication on flexible substrates. The presented results pave the way for upscaling the gSGFET technology towards large-scale, high-density μECoG-arrays, eventually capable of resolving neural activity down to a single neuron level, while simultaneously mapping large brain regions

Distortion-free sensing of neural activity using graphene transistors

Graphene solution-gated field-effect transistors (g-SGFETs) are promising sensing devices to transduce electrochemical potential signals in an electrolyte bath. However, distortion mechanisms in g-SGFET, which can affect signals of large amplitude or high frequency, have not been evaluated. Here, a detailed characterization and modeling of the harmonic distortion and non-ideal frequency response in g-SGFETs is presented. This accurate description of the input-output relation of the g-SGFETs allows to define the voltage- and frequency-dependent transfer functions, which can be used to correct distortions in the transduced signals. The effect of signal distortion and its subsequent calibration are shown for different types of electrophysiological signals, spanning from large amplitude and low frequency cortical spreading depression events to low amplitude and high frequency action potentials. The thorough description of the distortion mechanisms presented in this article demonstrates that g-SGFETs can be used as distortion-free signal transducers not only for neural sensing, but also for a broader range of applications in which g-SGFET sensors are used

Improved metal-graphene contacts for low-noise, high-density microtransistor arrays for neural sensing

Poor metal contact interfaces are one of the main limitations preventing unhampered access to the full potential of two-dimensional materials in electronics. Here we present graphene solution-gated field-effect-transistors (gSGFETs) with strongly improved linearity, homogeneity and sensitivity for small sensor sizes, resulting from ultraviolet ozone (UVO) contact treatment. The contribution of channel and contact region to the total device conductivity and flicker noise is explored experimentally and explained with a theoretical model. Finally, in-vitro recordings of flexible microelectrocorticography (μ-ECoG) probes were performed to validate the superior sensitivity of the UVO-treated gSGFET to brain-like activity. These results connote an important step towards the fabrication of high-density gSGFET μ-ECoG arrays with state-of-the-art sensitivity and homogeneity, thus demonstrating the potential of this technology as a versatile platform for the new generation of neural interfaces

Mitigating the noise of DESI mocks using analytic control variates

In order to address fundamental questions related to the expansion history of the Universe and its primordial nature with the next generation of galaxy experiments, we need to model reliably large-scale structure observables such as the correlation function and the power spectrum. Cosmological $N$-body simulations provide a reference through which we can test our models, but their output suffers from sample variance on large scales. Fortunately, this is the regime where accurate analytic approximations exist. To reduce the variance, which is key to making optimal use of these simulations, we can leverage the accuracy and precision of such analytic descriptions using Control Variates (CV). We apply two control variate formulations to mock catalogs generated in anticipation of upcoming data from the Dark Energy Spectroscopic Instrument (DESI) to test the robustness of its analysis pipeline. Our CV-reduced measurements, of the power spectrum and correlation function, both pre- and post-reconstruction, offer a factor of 5-10 improvement in the measurement error compared with the raw measurements from the DESI mock catalogs. We explore the relevant properties of the galaxy samples that dictate this reduction and comment on the improvements we find on some of the derived quantities relevant to Baryon Acoustic Oscillation (BAO) analysis. We also provide an optimized package for computing the power spectra and other two-point statistics of an arbitrary galaxy catalog as well as a pipeline for obtaining CV-reduced measurements on any of the AbacusSummit cubic box outputs. We make our scripts, notebooks, and benchmark tests against existing software publicly available and report a speed improvement of a factor of $\sim$10 for a grid size of $N_{\rm mesh} = 256^3$ compared with $\texttt{nbodykit}$.Comment: 15 pages, 9 figures, public package (for power spectrum and control variates estimation

Detecting and Characterizing Mg II absorption in DESI Survey Validation Quasar Spectra

In this paper we will present findings on the detection of Magnesium II (MgII, lambda = 2796 {\AA}, 2803 {\AA}) absorption systems observed in data from the Early Data Release (EDR) of the Dark Energy Spectroscopic Instrument (DESI). DESI is projected to obtain spectroscopy of approximately 3 million quasars (QSOs), of which over 99% are anticipated to be found at redshifts greater than z < 0.3, such that DESI would be able to observe an associated or intervening Mg II absorber illuminated by the background QSO. We have developed an autonomous supplementary spectral pipeline that detects such systems through an initial line-fitting process and then confirms line properties using a Markov Chain Monte Carlo (MCMC) sampler. Based upon both a visual inspection and the reanalysis of coadded observations, we estimate this sample of absorption systems to have a completeness of 82.56% and purity of 99.08%. As the spectra in which Mg II systems are detected are the result of coadding multiple observations, we can determine the sensitivity, and therefore completeness, of the sample by searching for known Mg II systems in coadded data with fewer observations (and therefore lower signal-to-noise). From a parent catalog containing 83,207 quasars, we detect a total of 23,921 Mg II absorption systems following a series of quality cuts. Extrapolating from this occurrence rate of 28.75% implies a catalog at the completion of the five-year DESI survey that contains over eight hundred thousand Mg II absorbers. The cataloging of these systems will enable significant further research as they carry information regarding circumgalactic medium (CGM) environments, the distribution of intervening galaxies, and the growth of metallicity across the redshift range 0.3 < z < 2.5.Comment: 12 pages, 7 figure

Remission of obesity and insulin resistance is not sufficient to restore mitochondrial homeostasis in visceral adipose tissue

Metabolic plasticity is the ability of a biological system to adapt its metabolic phenotype to different environmental stressors. We used a whole-body and tissue-specific phenotypic, functional, proteomic, metabolomic and transcriptomic approach to systematically assess metabolic plasticity in diet-induced obese mice after a combined nutritional and exercise intervention. Although most obesity and overnutrition-related pathological features were successfully reverted, we observed a high degree of metabolic dysfunction in visceral white adipose tissue, characterized by abnormal mitochondrial morphology and functionality. Despite two sequential therapeutic interventions and an apparent global healthy phenotype, obesity triggered a cascade of events in visceral adipose tissue progressing from mitochondrial metabolic and proteostatic alterations to widespread cellular stress, which compromises its biosynthetic and recycling capacity. In humans, weight loss after bariatric surgery showed a transcriptional signature in visceral adipose tissue similar to our mouse model of obesity reversion. Overall, our data indicate that obesity prompts a lasting metabolic fingerprint that leads to a progressive breakdown of metabolic plasticity in visceral adipose tissue

Differential body composition effects of protease inhibitors recommended for initial treatment of HIV infection: A randomized clinical trial

This article has been accepted for publication in Clinical Infectious Diseases ©2014 The Authors .Published by Oxford University Press on Clinical Infectious Disease 60.5. DOI: 10.1093/cid/ciu898Background. It is unclear whether metabolic or body composition effects may differ between protease inhibitor-based regimens recommended for initial treatment of HIV infection. Methods. ATADAR is a phase IV, open-label, multicenter randomized clinical trial. Stable antiretroviral-naive HIV-infected adults were randomly assigned to atazanavir/ritonavir 300/100 mg or darunavir/ritonavir 800/100 mg in combination with tenofovir/emtricitabine daily. Pre-defined end-points were treatment or virological failure, drug discontinuation due to adverse effects, and laboratory and body composition changes at 96 weeks. Results. At 96 weeks, 56 (62%) atazanavir/ritonavir and 62 (71%) darunavir/ritonavir patients remained free of treatment failure (estimated difference 8.2%; 95%CI -0.6 to 21.6); and 71 (79%) atazanavir/ritonavir and 75 (85%) darunavir/ritonavir patients remained free of virological failure (estimated difference 6.3%; 95%CI -0.5 to 17.6). Seven vs. five patients discontinued atazanavir/ritonavir or darunavir/ritonavir due to adverse effects. Total and HDL cholesterol similarly increased in both arms, but triglycerides increased more in atazanavir/ritonavir arm. At 96 weeks, body fat (estimated difference 2862.2 gr; 95%CI 726.7 to 4997.7; P=0.0090), limb fat (estimated difference 1403.3 gr; 95%CI 388.4 to 2418.2; P=0.0071), and subcutaneous abdominal adipose tissue (estimated difference 28.4 cm2; 95%CI 1.9 to 55.0; P=0.0362) increased more in atazanavir/ritonavir than in darunavir/ritonavir arm. Body fat changes in atazanavir/ritonavir arm were associated with higher insulin resistance. Conclusions. We found no major differences between atazanavir/ritonavir and darunavir/ritonavir in efficacy, clinically-relevant side effects, or plasma cholesterol fractions. However, atazanavir/ritonavir led to higher triglycerides and total and subcutaneous fat than darunavir/ritonavir and fat gains with atazanavir/ritonavir were associated with insulin resistanceThis is an Investigator Sponsored Research study. It was supported in part by research grants from Bristol‐Myers Squibb and Janssen‐Cilag; Instituto de Salud Carlos III (PI12/01217) and Red Temática Cooperativa de Investigación en SIDA G03/173 (RIS‐EST11), Ministerio de Ciencia e Innovación, Spain. (Registration number: NCT01274780; registry name: ATADAR; EUDRACT; 2010‐021002‐38)