A parametric approach for evaluating the stability of agricultural tractors using implements during side-slope activities

A methodological approach for evaluating a priori the stability of agricultural vehicles equipped with different mounted implements and operating on sloping hillsides is shown here. It uses a Matlab simulator in its first phase and, subsequently, the Response Surface Modelling (RSM) to evaluate the coefficients of a set of regression equations able to account for the Type-I and Type-II stability of the whole vehicle (tractor + implement with known dimensions and mass). The regression equations can give reliable punctual numeric estimations of the minimum value of the Roll Stability Index (RSI) and can verify the existence of a Type-I equilibrium without the need of using the simulator or knowing any detail about the model implemented in it. The same equations can also be used to generate many intuitive graphs (\u201cequilibrium maps\u201d) useful to verify quickly the possible overturning of the vehicle. A case-study concerning a 4-wheel drive articulated tractor is then presented to show the potential of the approach and how using its tools. The tractor has been studied in three scenarios, differing on where the implement has to be connected to the tractor (1: frontally; 2: frontally-laterally; 3: in the back). After performing a series of simulations, a set of polynomial models (with 6 independent variables) has been created and verified. Then, these models were used, together with the related equilibrium maps, to predict the stability of 8 implements for scenario 1, 7 implements for scenario 2, and 3 implements for scenario 3, evidencing in particular the danger of using a lateral shredder with a mass greater than 245 kg. The proposed approach and its main outcomes (i.e., the regression equations and the equilibrium maps) can give an effective contribution to the preventive safety of the tractor driver, so it could be useful to integrate it in the homologation procedures for every agricultural vehicle and to include the resulting documentation within the tractor logbook

Simultaneous calibrated prediction intervals for time series

This paper deals with simultaneous prediction for time series models. In particular, it presents a simple procedure which gives well-calibrated simultaneous predictive intervals with coverage probability equal or close to the target nominal value. Although the exact computation of the proposed intervals is usually not feasible, an approximation can be easily obtained by means of a suitable bootstrap simulation procedure. This new predictive solution is much simpler to compute than those ones already proposed in the literature based on asymptotic calculations. An application of the bootstrap calibrated procedure to first order autoregressive models is presented

Low Arousal Threshold Estimation Predicts Failure of Mandibular Advancement Devices in Obstructive Sleep Apnea Syndrome

Introduction: The treatment of choice for obstructive sleep apnea syndrome (OSAS) is continuous positive airway pressure (CPAP). However, CPAP is usually poorly tolerated and mandibular advancement devices (MADs) are an alternative innovative therapeutic approach. Uncertainty still remains as to the most suitable candidates for MAD. Herein, it is hypothesized that the presence of low arousal threshold (low ArTH) could be predictive of MAD treatment failure. Methods: A total of 32 consecutive patients, with OSAS of any severity, who preferred an alternate therapy to CPAP, were treated with a tailored MAD aimed at obtaining 50% of their maximal mandibular advancement. Treatment response after 6 months of therapy was defined as AHI 58.3%. Results: There were 25 (78.1%) responders (p-value < 0.01) at 6 months. Thirteen patients (40.6%) in the non-severe group reached AHI lower than 5 events per hour. MAD treatment significantly reduced the median AHI in all patients from a median value of 22.5 to 6.5 (74.7% of reduction, p-value < 0.001). The mandibular advancement device reduced AHI, whatever the disease severity. A significant higher reduction of Delta AHI, after 6 months of treatment, was found for patients without low ArTH. Conclusions: Low ArTH at baseline was associated with a poorer response to MAD treatment and a lower AHI reduction at 6 months. A non-invasive assessment of Low ArTH can be performed through the Edwards' score, which could help to identify an endotype with a lower predicted response to oral appliances in a clinical setting

A Tracked Mobile Robotic Lab for Monitoring the Plants Volume and Health

9noPrecision agriculture has been increasingly recognized for its potential ability to improve agricultural productivity, reduce production cost, and minimize damage to the environment. In this work, the current stage of our research in developing a mobile platform equipped with different sensors for orchard monitoring and sensing is presented. In particular, the mobile platform is conceived to monitor and assess both the geometric and volumetric conditions as well as the health state of the canopy. To do so, different sensors have been integrated and efficient data-processing algorithms implemented for a reliable crop monitoring. Experimental tests have been performed allowing to obtain both a precise volume reconstruction of several plants and an NDVI mapping suitable for vegetation state evaluations.openopenopenBietresato, M; Carabin, G; D’Auria, D; Gallo, R; Gasparetto, A.; Ristorto, G; Mazzetto, F; Vidoni, R; Scalera, L.Bietresato, M; Carabin, G; D’Auria, D; Gallo, R; Gasparetto, Alessandro; Ristorto, G; Mazzetto, F; Vidoni, R; Scalera, Lorenz

MitoNeoD:a mitochondria-targeted superoxide probe

Mitochondrial superoxide (O2⋅−) underlies much oxidative damage and redox signaling. Fluorescent probes can detect O2⋅−, but are of limited applicability in vivo, while in cells their usefulness is constrained by side reactions and DNA intercalation. To overcome these limitations, we developed a dual-purpose mitochondrial O2⋅− probe, MitoNeoD, which can assess O2⋅− changes in vivo by mass spectrometry and in vitro by fluorescence. MitoNeoD comprises a O2⋅−-sensitive reduced phenanthridinium moiety modified to prevent DNA intercalation, as well as a carbon-deuterium bond to enhance its selectivity for O2⋅− over non-specific oxidation, and a triphenylphosphonium lipophilic cation moiety leading to the rapid accumulation within mitochondria. We demonstrated that MitoNeoD was a versatile and robust probe to assess changes in mitochondrial O2⋅− from isolated mitochondria to animal models, thus offering a way to examine the many roles of mitochondrial O2⋅−production in health and disease

The challenge of sharing data in cooperation projects: cause for reflection.

The collection of data and  their management  remain a never-ending challenge within projects carried out in low-income countries.  Data collection requires high investments, and even if great efforts have been done in building tools for data sharing, these processes need to be improved at local level in developing countries. Data are valuable items  for developing strategies leading to more effective local development. The CeTAmb LAB, on the basis of its experience, proposes a reflection on the role of the academia, which is based on principles of capacity building and sharing knowledge, in promoting the importance of data collection, conservation and sharing

Evaluation of noise regression techniques in resting-state fMRI studies using data of 434 older adults

Subject motion is a well-known confound in resting-state functional MRI (rs-fMRI) and the analysis of functional connectivity. Consequently, several clean-up strategies have been established to minimize the impact of subject motion. Physiological signals in response to cardiac activity and respiration are also known to alter the apparent rs-fMRI connectivity. Comprehensive comparisons of common noise regression techniques showed that the Independent Component Analysis based strategy for Automatic Removal of Motion Artifacts (ICA-AROMA) was a preferred pre-processing technique for teenagers and adults. However, motion and physiological noise characteristics may differ substantially for older adults. Here, we present a comprehensive comparison of noise-regression techniques for older adults from a large multi-site clinical trial of exercise and intensive pharmacological vascular risk factor reduction. The Risk Reduction for Alzheimer\u27s Disease (rrAD) trial included hypertensive older adults (60-84 years old) at elevated risk of developing Alzheimer\u27s Disease (AD). We compared the performance of censoring, censoring combined with global signal regression, non-aggressive and aggressive ICA-AROMA, as well as the Spatially Organized Component Klassifikator (SOCK) on the rs-fMRI baseline scans from 434 rrAD subjects. All techniques were rated based on network reproducibility, network identifiability, edge activity, spatial smoothness, and loss of temporal degrees of freedom (tDOF). We found that non-aggressive ICA-AROMA did not perform as well as the other four techniques, which performed table with marginal differences, demonstrating the validity of these techniques. Considering reproducibility as the most important factor for longitudinal studies, given low false-positive rates and a better preserved, more cohesive temporal structure, currently aggressive ICA-AROMA is likely the most suitable noise regression technique for rs-fMRI studies of older adults