The effects of environmental temperature changes on the EKG of the squirrel monkey /Saimiri sciureus/

Environmental temperature effects on EKG of squirrel monkey - animal study of heart rate and T-wave amplitud

Modification of vestibular sensitivity in the rat

Vestibular sensitivity and associated locomotor responses of rats in rotating environmen

Experimental and numerical assessment of fibre bridging toughening effects on the compressive behaviour of delaminated composite plates

Increasing the Mode I inter-laminar fracture toughness of composite laminates can contribute to slowing down delamination growth phenomena, which can be considered one of the most critical damage mechanisms in composite structures. Actually, the Mode I interlaminar fracture toughness (GIc) in fibre-reinforced composite materials has been found to considerably increase with the crack length when the fibre bridging phenomenon takes place. Hence, in this paper, the fibre bridging phenomenon has been considered as a natural toughening mechanism able to replace embedded metallic or composite reinforcements, currently used to increase tolerance to inter-laminar damage. An experimental/numerical study on the influence of delamination growth on the compressive behaviour of fibre-reinforced composites characterised by high sensitivity to the fibre bridging phenomenon has been performed. Coupons, made of material systems characterised by a variable toughness related to a high sensitivity to the fibre bridging phenomenon and containing artificial through-the-width delaminations, were subjected to a compressive mechanical test and compared to coupons made of standard material system with constant toughness. Out-of-plane displacements and strains were monitored during the compression test by means of strain gauges and digital image correlation to assess the influence of fibre bridging on delamination buckling, delamination growth and on the global buckling of the specimens, including buckling shape changes. Experimental data were combined with a numerical study, performed by means of a virtual crack closure technique based procedure, named SMart Time XB-Fibre Bridging (SMXB-FB), able to mimic the crack bridging effect on the toughness properties of the material system. The combination of numerical results and experimental data has allowed the deformations and the buckling shape changes to be correlated to the onset and evolution of damage and, hence, contributes to improving the knowledge on the interaction of the failure mechanisms in the investigated composite specimens

Workload measurement in a communication application operated through a P300-based brain-computer interface

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A Multicentre Study: The Use of Micrografts in the Reconstruction of Full-Thickness Posttraumatic Skin Defects of the Limbs - A Whole Innovative Concept in Regenerative Surgery

The skin graft is a surgical technique commonly used in the reconstructive surgery of the limbs, in order to repair skin loss, as well as to repair the donor area of the flaps and cover the dermal substitutes after engraftment. The unavoidable side effect of this technique consists of unaesthetic scars. In order to achieve the healing of posttraumatic ulcers by means of tissue regeneration and to avoid excessive scarring, a new innovative technology based on the application of autologous micrografts, obtained by Rigenera technology, was reported. This technology was able to induce tissue repair by highly viable skin micrografts of 80 micron size achieved by a mechanical disaggregation method. The specific cell population of these micrografts includes progenitor cells, which in association with the fragment of the Extracellular Matrix (ECM) and growth factors derived by patients' own tissue initiate biological processes of regeneration enhancing the wound healing process. We have used this technique in 70 cases of traumatic wounds of the lower and upper limbs, characterized by extensive loss of skin substance and soft tissue. In all cases, we have applied the Rigenera protocol using skin micrografts, achieving in 69 cases the complete healing of wounds in a period between 35 and 84 days. For each patient, the reconstructive outcome was evaluated weekly to assess the efficacy of this technique and any arising complication. A visual analogue scale (VAS) was administered to assess the amount of pain felt after the micrografts' application, whereas we evaluated the scars according to the Vancouver scale and the wound prognosis according to Wound Bed Score. We have thus been able to demonstrate that Rigenera procedure is very effective in stimulating skin regeneration, while reducing the outcome scar

Can Social Policies Improve Health? A Systematic Review and Meta-Analysis of 38 Randomized Trials.

Policy Points Social policies might not only improve economic well-being, but also health. Health policy experts have therefore advocated for investments in social policies both to improve population health and potentially reduce health system costs. Since the 1960s, a large number of social policies have been experimentally evaluated in the United States. Some of these experiments include health outcomes, providing a unique opportunity to inform evidence-based policymaking. Our comprehensive review and meta-analysis of these experiments find suggestive evidence of health benefits associated with investments in early life, income support, and health insurance interventions. However, most studies were underpowered to detect health outcomes. CONTEXT: Insurers and health care providers are investing heavily in nonmedical social interventions in an effort to improve health and potentially reduce health care costs. METHODS: We performed a systematic review and meta-analysis of all known randomized social experiments in the United States that included health outcomes. We reviewed 5,880 papers, reports, and data sources, ultimately including 61 publications from 38 randomized social experiments. After synthesizing the main findings narratively, we conducted risk of bias analyses, power analyses, and random-effects meta-analyses where possible. Finally, we used multivariate regressions to determine which study characteristics were associated with statistically significant improvements in health outcomes. FINDINGS: The risk of bias was low in 17 studies, moderate in 11, and high in 33. Of the 451 parameter estimates reported, 77% were underpowered to detect health outcomes. Among adequately powered parameters, 49% demonstrated a significant health improvement, 44% had no effect on health, and 7% were associated with significant worsening of health. In meta-analyses, early life and education interventions were associated with a reduction in smoking (odds ratio [OR] = 0.92, 95% confidence interval [CI] 0.86-0.99). Income maintenance and health insurance interventions were associated with significant improvements in self-rated health (OR = 1.20, 95% CI 1.06-1.36, and OR = 1.38, 95% CI 1.10-1.73, respectively), whereas some welfare-to-work interventions had a negative impact on self-rated health (OR = 0.77, 95% CI 0.66-0.90). Housing and neighborhood trials had no effect on the outcomes included in the meta-analyses. A positive effect of the trial on its primary socioeconomic outcome was associated with higher odds of reporting health improvements. We found evidence of publication bias for studies with null findings. CONCLUSIONS: Early life, income, and health insurance interventions have the potential to improve health. However, many of the included studies were underpowered to detect health effects and were at high or moderate risk of bias. Future social policy experiments should be better designed to measure the association between interventions and health outcomes

Supervised machine learning on Galactic filaments. Revealing the filamentary structure of the Galactic interstellar medium

Context. Filaments are ubiquitous in the Galaxy, and they host star formation. Detecting them in a reliable way is therefore key towards our understanding of the star formation process. Aims: We explore whether supervised machine learning can identify filamentary structures on the whole Galactic plane. Methods: We used two versions of UNet-based networks for image segmentation. We used H2 column density images of the Galactic plane obtained with Herschel Hi-GAL data as input data. We trained the UNet-based networks with skeletons (spine plus branches) of filaments that were extracted from these images, together with background and missing data masks that we produced. We tested eight training scenarios to determine the best scenario for our astrophysical purpose of classifying pixels as filaments. Results: The training of the UNets allows us to create a new image of the Galactic plane by segmentation in which pixels belonging to filamentary structures are identified. With this new method, we classify more pixels (more by a factor of 2 to 7, depending on the classification threshold used) as belonging to filaments than the spine plus branches structures we used as input. New structures are revealed, which are mainly low-contrast filaments that were not detected before. We use standard metrics to evaluate the performances of the different training scenarios. This allows us to demonstrate the robustness of the method and to determine an optimal threshold value that maximizes the recovery of the input labelled pixel classification. Conclusions: This proof-of-concept study shows that supervised machine learning can reveal filamentary structures that are present throughout the Galactic plane. The detection of these structures, including low-density and low-contrast structures that have never been seen before, offers important perspectives for the study of these filaments