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Metastability stems from the finite lifetime of a state when a lower-energy configuration is available but only by tunnelling through an energy barrier. It is observed in many natural situations, including in chemical processes and in electron field ionization. In classical many-body systems, metastability naturally emerges in the presence of a first-order phase transition. A prototypical example is a supercooled vapour. The extension to quantum field theory and quantum many-body systems has attracted significant interest in the context of statistical physics, protein folding and cosmology, for which thermal and quantum fluctuations are expected to trigger the transition from the metastable state (false vacuum) to the ground state (true vacuum) through the probabilistic nucleation of spatially localized bubbles. However, the long-standing theoretical progress in estimating the relaxation rate of the metastable field through bubble nucleation has not been validated experimentally. Here we experimentally observe bubble nucleation in isolated and coherently coupled atomic superfluids, and we support our observations with numerical simulations. The agreement between our observations and an analytic formula based on instanton theory confirms our physical understanding of the decay process and promotes coherently coupled atomic superfluids as an ideal platform to investigate out-of-equilibrium quantum field phenomena. The transition from a metastable state to the ground state in classical many-body systems is mediated by bubble nucleation. This transition has now been experimentally observed in a quantum setting using coupled atomic superfluids.

A hallmark of the ERK1/2 functioning is their nuclear translocation, which is mainly required for the induction of proliferation. Activated ERK1/2 molecules that remain in the cytoplasm initiate other activities, including immediate feedback loops. Prevention of the nuclear translocation should therefore inhibit proliferation, without affecting cytoplasm-induced cellular processes. Here we present an NTS-derived myristoylated phosphomimetic peptide, which blocks the interaction of importin7 and ERK1/2, and consequently the nuclear translocation of the latter. In culture, the peptide induces apoptosis of melanoma cells inhibits the viability of other cancer cells, but has no effect on non-transformed, immortalized cells. It even inhibits the viability of PLX4032- and U0126-resistant melanoma cells. In xenograft models, the peptide inhibits several cancers, and acts much better than PLX4032 in preventing melanoma recurrence. This study provides a proof of concept for using the nuclear translocation of ERK1/2 as a drug target for the combat of various ERK1/2-related cancers. The extracellular signal-regulated kinase 1/2 (ERK1/2) cascade is involved in the induction and maintenance of cancers. Here the authors design an ERK-derived peptide that blocks ERK nuclear import, thus proposing a novel approach to treat tumours with mutational activation of the ERK pathway.

Study on static in-situ curing characteristics of CFRP based on near infrared laser The quick curing method of carbon fibre reinforced plastics (CFRP) is one of the hotspots in current research. A static in-situ curing method for CFRP prepreg based on near-infrared laser was put forward in this study. The in-situ curing structural characteristics and the mechanism of CFRP were investigated through real-time surface temperature measurement, COMSOL temperature field simulation, 3D measurement of curing morphology and resin curing degree test. The thermal conductivity of the CFRP along the fiber direction is considerably higher than that along the perpendicular fiber direction. As a result, the temperature profile in the plane takes on an elliptical shape. During the transfer, the temperature field gradually decreases, resulting in an ellipsoidal 3D high-temperature distribution. The different shrinkage phenomena in the different curing regions between the layers lead to an irregular ellipsoidal solidification morphology of the unidirectional CFRP. The temperature in the center of the heat affected zone increases as a power exponential function with time. The area and depth of the heat-affected zone increases with the laser power, and the curing area is positively correlated with the degree of curing. As a result, curing temperature governing equations based on laser power and layer thickness have been proposed, while relationship equations based on laser power, curing depth and curing morphology have been developed. In addition, prediction equations based on curing morphology have been developed for curing degree, in order to achieve precise curing of CFRP.

The benefits of soil organic input on crop yields have long been discussed, yet details of their relationship remain controversial. This study considers the effects of different residue management on crop performance as assessed by yield and nitrogen use efficiency (NUE). Three residue management (residue removal, residue incorporation, and residue incorporation + added poultry manure), combined with five levels of N application, were studied in a long-term experiment starting in 1966. Crop residue incorporation improved maize yield by 12% (nutritional effect) and sugar beet yield by 16% (non-nutritional), and the combination of crop residue incorporation with added poultry manure increased both winter wheat and sugar beet yields by 8% (nutritional effect). The NUE values of mineral fertiliser were almost three-fold those of residues and the combination of residue with poultry manure, except in sugar beet and maize, where NUE of mineral fertilizer approached those observed for residues (0.44 vs 0.45, on average). In wheat, NUE for residue incorporation with added poultry manure was nearly double the NUE for residues alone. Residue management effects depended on crop type; spring-sown crops showing stronger effects than those sown in autumn. Residues primarily produced a nutritional effect, suggesting that they decomposed within 1 year. While residue use offers little potential for soil improvement, it does reduce the need for fertilisers.

•Several studies recognized Argentine tango as effective in Idiopathic Parkinson Disease.•Argentine tango is well described in studies investigating Idiopathic Parkinson Disease.•Complete description of the intervention procedures is necessary to promote clinical practice. To analyse the content of the interventions reported in studies investigating the applicability and efficacy of Argentine tango in participants with Idiopathic Parkinson Disease. Independent reviewers searched databases (PubMed, CINAHL, EMBASE, PsycINFO, and PEDro) from their inception to November 2019. Eligible studies were randomised, controlled and uncontrolled clinical trials, and case reports. The Template for Intervention Description and Replication guidelines and checklist were used to assess quality and quantity of the content of Argentine tango interventions’ description. We found 21 papers investigating the applicability and efficacy of Argentine tango in participants with Idiopathic Parkinson Disease. Completeness of the reporting of intervention was satisfying. The intervention is intended to affect a variety of aspects of functioning relevant to individuals with Idiopathic Parkinson Disease. Detailed information on the intervention's procedure and dosing is usually provided. The delivery of the Tango dance program was predominantly extensive; however, the intervention has been provided with various approaches and showed to be very adaptable. Attrition- and adherence- rates described are acceptable. The Adapted Tango dance program is the earliest and most researched modality of tango intervention in participants with Idiopathic Parkinson Disease. Argentine tango is appropriately described in the studies investigating the applicability and efficacy of the intervention in participants with Idiopathic Parkinson Disease. However, the reporting could be ameliorated.

Background:Systemic vasculitides are a group of inflammatory multisystem diseases with recurrent relapses and chronic damage due to disease and its treatments. The extent to which having this condition impacts the psychological health of patients is yet to be fully understood.Objectives:To quantify the psychological impact of living with systemic vasculitides.Methods:We cross-sectionally evaluated a cohort of patients with systemic vasculitides seen at diagnosis or follow-up in our center, between April 1st and December 31st, 2023. Data collected from each patient included their demographic and clinical data, as well as their medical history.We administered the symptom checklist revised (SCL-90-R) to measure distress related to 9 psychological dimensions, i.e. somatization (SOM), obsessive compulsion (OC), interpersonal sensitivity (IS), depression (DEP), anxiety (ANX), hostility (HOS), phobic anxiety (PHOB), paranoid ideation (PAR), psychoticism (PSY), and providing 3 global indices of distress, i.e. global severity index (GSI, the average symptom intensity), positive symptom distress index (PSDI, average level of distress for those items that were endorsed), and positive symptom total (PST, i.e. total symptoms endorsed). Distress was categorized in 4 intensity levels (null, low, moderate and high) with respect to the Italian reference population. We applied loglinear model to investigate if different vasculitis vessel types correlated with different psychological distress.Results:By using the SCL-90-R checklist, we screened a total of 171 patients affected by systemic vasculitides (females 48.5%, mean age 65 years old, range: 21-88): 64% had small vessel vasculitis (SVV, of which 89% were ANCA-associated vasculitides), 29% had large vessel vasculitis (LVV, of which 79% were giant cell arteritis), 7% had variable vessel vasculitis (VVV, Behcet’s disease).Eight % of patients reported moderate-to-high intensity for PAR and HOS, while more than 20% for DEP and ANX. Thirty % of patients reported moderate-to-high intensity for SOM, which may be expected considering the confounding effect of being affected by systemic vasculitides. Less than 5% reported no symptoms in any dimensions, while 45% reported at least one dimension with moderate-to-high intensity, and 13% more than 4 dimensions (as shown in Figure 1A, representing percentage of outpatient with psychological distress and its intensity for each of the 9 dimensions and 3 global indexes).Active disease (as assessed by Birmingham vasculitis activity score >0) was associated with DEP, ANX, PSY, and PST (p<0.05); prednisone ≥5 mg/day was associated with ANX (p<0.05), while no dimensions were associated with different categories of immunosuppressive therapies. Notably, severe damage (Vasculitis Damage Index ≥5) associated with SOM, OC, DEP, ANX, GSI, and PSDI (p<0.05).Loglinear models showed associations of different vasculitis vessel types only with DEP (p=0.01) and SOM (p=0.03), as shown in the radar plots (Figure 1B).Figue 1.Conclusion:Patients affected by systemic vasculitides showed psychological distress in various symptomatic dimensions with respect to the Italian reference population, showing significant association with disease activity, glucocorticoid use, vasculitis vessel types, and particularly with severe damage. Our findings showed the need for psychological screening to identify distress due to vasculitis, aiming to reduce it with psychological interventions.REFERENCES:[1] Derogatis, L.R. and Unger, R. Symptom Checklist-90-Revised (2010).Acknowledgements:NIL.Disclosure of Interests:None declared.

This research provides an insight on the performances of machine learning (ML)-based algorithms for the estimation of the energy consumption in metal forming processes and is applied to the radial-axial ring rolling process. To define the mutual influence between ring geometry, process settings, and ring rolling mill geometries with the resulting energy consumption, measured in terms of the force integral over the processing time (FIOT), FEM simulations have been implemented in the commercial SW Simufact Forming 15. A total of 380 finite element simulations with rings ranging from 650 mm < DF < 2000 mm have been implemented and constitute the bulk of the training and validation datasets. Both finite element simulation settings (input), as well as the FI (output), have been utilized for the training of eight machine learning models, implemented with Python scripts. The results allow defining that the Gradient Boosting (GB) method is the most reliable for the FIOT prediction in forming processes, being its maximum and average errors equal to 9.03% and 3.18%, respectively. The trained ML models have been also applied to own and literature experimental cases, showing a maximum and average error equal to 8.00% and 5.70%, respectively, thus proving once again its reliability.

In everyday life, the successful monitoring of behavior requires continuous updating of the effectiveness of motor acts; one crucial step is becoming aware of the movements one is performing. We studied the anatomical distribution of lesions in right-brain-damaged hemiplegic patients, who obstinately denied their motor impairment, claiming that they could move their paralyzed limbs. Denial was associated with lesions in areas related to the programming of motor acts, particularly Brodmann's premotor areas 6 and 44, motor area 4, and the somatosensory cortex. This association suggests that monitoring systems may be implemented within the same cortical network that is responsible for the primary function that has to be monitored.

Sheets’ buckling instability, also known as oil canning, is an issue that characterizes the resistance to denting in thin metal panels. The oil canning phenomenon is characterized by a depression in the metal sheet, caused by a local buckling, which is a critical design issue for aesthetic parts, such as automotive outer panels. Predicting the buckling instability during the design stage is not straightforward since the shape of the component might change several times before the part is sent to production and can actually be tested. To overcome this issue, this research presents a robust prediction model based on the convolutional neural network (CNN) to estimate the buckling instability of automotive sheet metal panels, based on the major, minor, and Gaussian surface curvatures. The training dataset for the CNN model was generated by implementing finite element analysis (FEA) of the outer panels of various commercial vehicles, for a total of twenty panels, and by considering different indentation locations on each panel. From the implemented simulation models the load-stroke curves were exported and utilized to determine the presence, or absence, of buckling instability and to determine its magnitude. Moreover, from the computer aided design (CAD) files of the relevant panels, the three considered curvatures on the tested indentation points were acquired as well. All the positions considered in the FEA analyses were backed up by industrial experiments on the relevant panels in their assembled position, allowing to validate their reliability. The combined correlation of curvatures and load-displacement curves allowed correlating the geometrical features that create the conditions for buckling instability to arise and was utilized to train the CNN algorithm, defined considering 13 convolution layers and 5 pooling layers. The trained CNN model was applied to another automotive frame, not used in the training process, and the prediction results were compared with experimental indentation tests. The overall accuracy of the CNN model was calculated to be 90.1%, representing the reliability of the proposed algorithm of predicting the severity of the buckling instability for automotive sheet metal panels.

The identification of the source of a specific soil sample is a crucial step in forensic investigations. Rapid advances in next generation sequencing (NGS) technology and the strong reduction of the cost of sequencing have recently opened new perspectives. In the present work a metabarcoding approach has been successfully applied to forensic and environmental soil samples, allowing the accurate and sensitive analysis of microflora (mfDNA), plants, metazoa, and protozoa DNA. The identification of the biological component by DNA metabarcoding is a strong element for the discrimination of samples geologically very similar but coming for distinct environments.