Changes in Crude Protein and Fiber Contents of Small Grain Cereals for Forage over Time

Oat, triticale, wheat and barley are small grain cereals used as forage in many temperate Mexican regions. The objective was to determine crude protein and van Soest fiber contents of these forages cut at 80, 96, 108, 121, 138 and 153 days after seeding. Cultivars used were: Chihuahua (OC) for oat; Arne (TA), Bicentenario (TB) and Siglo XXI (TS) for triticale; Saturno (WS) for wheat; and San Marcos (BSM) for barley. Experiment was under greenhouse conditions from November 2015 to May 2016. Crude protein (CP), neutral (NDF) and acid (ADF) detergents fibers were determined on the forage harvested at each time. Statistical analysis was by linear regression with cultivar as a dummy variable (R2= 0.5843 to 0.6861), response variables were CP, NDF and ADF contents over days after seeding (R2≥ 0.7693), the model included first grade interaction. Models developed were compared based on the slopes calculated. First grade interaction was significant (p\u3c 0.05) in CP due to the pattern change in TS, and in NDF due to the pattern change in OC and in ADF due to the pattern change in TA. So that, individual models and coefficient confident intervals were developed for each species and cultivar to compare them and to declare similarities or differences at p\u3c 0.05. Overall, CP decreased (p\u3e 0.05) from 0.11 to 0.39; while NDF and ADF increased (p\u3e 0.05) from 0.60 to 1.10, and from 0.20 to 0.83 percentage units day-1 respectively. It was concluded that crude protein, neutral and acid detergent fiber contents in small grain cereals are not dependent on harvesting time when measured at development stages close to physiological maturity

Gaussianization of LA-ICP-MS features to improve calibration in forensic glass comparison

The forensic comparison of glass aims to compare a glass sample of an unknown source with a control glass sample of a known source. In this work, we use multi-elemental features from Laser Ablation Inductively Coupled Plasma with Mass Spectrometry (LA-ICP-MS) to compute a likelihood ratio. This calculation is a complex procedure that generally requires a probabilistic model including the within-source and betweensource variabilities of the features. Assuming the within-source variability to be normally distributed is a practical premise with the available data. However, the between-source variability is generally assumed to follow a much more complex distribution, typically described with a kernel density function. In this work, instead of modeling distributions with complex densities, we propose the use of simpler models and the introduction of a data pre-processing step consisting on the Gaussianization of the glass features. In this context, to obtain a better fit of the features with the Gaussian model assumptions, we explore the use of different normalization techniques of the LA-ICP-MS glass features, namely marginal Gaussianization based on histogram matching, marginal Gaussianization based on Yeo-Johnson transformation and a more complex joint Gaussianization using normalizing flows. We report an improvement in the performance of the Likelihood Ratios computed with the previously Gaussianized feature vectors, particularly relevant in their calibration, which implies a more reliable forensic glass comparisonThis work has been supported by the Spanish Ministerio de Ciencia e Innovación through grant PID2021-125943OB-I0

Velocity Loss Thresholds Reliably Control Kinetic and Kinematic Outputs during Free Weight Resistance Training.

Exercise velocity and relative velocity loss thresholds (VLTs) are commonly used in velocity-based resistance training. This study aims to quantify the between-day reliability of 10%, 20%, and 30% VLTs on kinetic and kinematic outputs, changes in external load, and repetition characteristics in well-trained athletes. Using a repeated, counter-balanced crossover design, twelve semi-professional athletes completed five sets of the back squat with an external load corresponding to a mean concentric velocity of ~0.70 m·s-1 and a VLT applied. The testing sessions were repeated after four weeks of unstructured training to assess the long-term reliability of each VLT. A coefficient of variation (CV) 10% (CV: 11.14-14.92%). Alternatively, the repetitions completed within each set showed large variation (CV: 18.92-67.49%). These findings demonstrate that by utilizing VLTs, kinetic and kinematic outputs can be prescribed and replicated across training mesocycles. Thus, for practitioners wishing to reliably control the kinetic and kinematic stimulus that is being applied to their athletes, it is advised that a velocity-based approach is used

Near-Infrared Polarimetric Adaptive Optics Observations of NGC 1068: A torus created by a hydromagnetic outflow wind

We present J' and K' imaging linear polarimetric adaptive optics observations of NGC 1068 using MMT-Pol on the 6.5-m MMT. These observations allow us to study the torus from a magnetohydrodynamical (MHD) framework. In a 0.5" (30 pc) aperture at K', we find that polarisation arising from the passage of radiation from the inner edge of the torus through magnetically aligned dust grains in the clumps is the dominant polarisation mechanism, with an intrinsic polarisation of 7.0%$\pm$2.2%. This result yields a torus magnetic field strength in the range of 4$-$82 mG through paramagnetic alignment, and 139$^{+11}_{-20}$ mG through the Chandrasekhar-Fermi method. The measured position angle (P.A.) of polarisation at K$'$ is found to be similar to the P.A. of the obscuring dusty component at few parsec scales using infrared interferometric techniques. We show that the constant component of the magnetic field is responsible for the alignment of the dust grains, and aligned with the torus axis onto the plane of the sky. Adopting this magnetic field configuration and the physical conditions of the clumps in the MHD outflow wind model, we estimate a mass outflow rate $\le$0.17 M$_{\odot}$ yr$^{-1}$ at 0.4 pc from the central engine for those clumps showing near-infrared dichroism. The models used were able to create the torus in a timescale of $\geq$10$^{5}$ yr with a rotational velocity of $\leq$1228 km s$^{-1}$ at 0.4 pc. We conclude that the evolution, morphology and kinematics of the torus in NGC 1068 can be explained within a MHD framework.Comment: 14 pages, 4 figures, Accepted by MNRA

Possible Patient Early Diagnosis by Ultrasonic Noninvasive Estimation of Thermal Gradients into Tissues Based on Spectral Changes Modeling

To achieve a precise noninvasive temperature estimation, inside patient tissues, would open promising research fields, because its clinic results would provide early-diagnosis tools. In fact, detecting changes of thermal origin in ultrasonic echo spectra could be useful as an early complementary indicator of infections, inflammations, or cancer. But the effective clinic applications to diagnosis of thermometry ultrasonic techniques, proposed previously, require additional research. Before their implementations with ultrasonic probes and real-time electronic and processing systems, rigorous analyses must be still made over transient echotraces acquired from well-controlled biological and computational phantoms, to improve resolutions and evaluate clinic limitations. It must be based on computing improved signal-processing algorithms emulating tissues responses. Some related parameters in echo-traces reflected by semiregular scattering tissues must be carefully quantified to get a precise processing protocols definition. In this paper, approaches for non-invasive spectral ultrasonic detection are analyzed. Extensions of author's innovations for ultrasonic thermometry are shown and applied to computationally modeled echotraces from scattered biological phantoms, attaining high resolution (better than 0.1°C). Computer methods are provided for viability evaluation of thermal estimation from echoes with distinct noise levels, difficult to be interpreted, and its effectiveness is evaluated as possible diagnosis tool in scattered tissues like liver

Exploring host genetic polymorphisms involved in SARS-CoV infection autcomes: implications for personalized medicine in COVID-19

Objective. To systematically explore genetic polymorphisms associated with the clinical outcomes in SARS-CoV infection in humans. Methods. This comprehensive literature search comprised available English papers published in PubMed/Medline and SCOPUS databases following the PRISMA-P guidelines and PICO/AXIS criteria. Results. Twenty-nine polymorphisms located in 21 genes were identified as associated with SARS-CoV susceptibility/resistance, disease severity, and clinical outcomes predominantly in Asian populations. Thus, genes implicated in key pathophysiological processes such as the mechanisms related to the entry of the virus into the cell and the antiviral immune/inflammatory responses were identified. Conclusions. Although caution must be taken, the results of this systematic review suggest that multiple genetic polymorphisms are associated with SARS-CoV infection features by affecting virus pathogenesis and host immune response, which could have important applications for the study and understanding of genetics in SARS-CoV-2/COVID-19 and for personalized translational clinical practice depending on the population studied and associated environments

A distributed virtual MIMO coalition formation framework for energy efficient wireless networks

International audienceIn this paper, we consider a low complexity virtual Multiple-input Multiple-output (MIMO) coalition formation algorithm. The goal is to obtain improvements in energy efficiency by forming multi-antenna virtual arrays for information transmission in the uplink. Virtual arrays are formed by finding a stable match between single antenna devices such as mobile station (MS) and relay stations (RS) by using a game theoretic approach derived from the concept of the college admissions problem. We focus on enhancing the mobile station (MS) performance by forming virtual coalitions with the RSs. Thus, power savings are obtained through multi-antenna arrays by implementing the concepts of spatial diversity and spatial multiplexing for uplink transmission. We focus on optimizing the overall consumed power rather than the transmitted power of the network devices. Furthermore, it is shown analytically and by simulations that when overall consumed power is considered as an optimization metric, the energy efficiency of the single antennas devices is not always improved by forming a virtual MIMO array. Hence, single antenna devices may prefer to transmit on their own when channel conditions are favorable. In addition, the simulation results show that our proposed framework provides comparable energy savings and a lower implementation complexity when compared to a centralized exhaustive search approach that is coordinated from the BS