The stability of the ion temperature gradient modes is investigated using the kinetic ion response without expansions in ωD/ω. A systematic parameter study is carried out using a low-beta circular flux surface equilibrium in order to determine the stability boundaries in ηi vs εn space (ηi=d ln Ti/ d ln n, εn=Ln/R). Particular attention is devoted to the consequences of the presence of these modes for anomalous ion transport.

An analysis of the radial structure of the ion-temperature-gradient-driven mode is presented and the dependence of the radial correlation length L, on parameters such as magnetic shear is discussed. It is found that L, decreases algebraically with increasing shear for moderate to large shear values, and it decreases exponentially with decreasing shear for low shear values. These results seem in qualitative agreement with several experiments which observe strong reduction of the transport coefficients close to the magnetic axis.

The presented meta-analysis demonstrates that FNAC is able to detect approximately one-half of MTC lesions. These findings suggest that other techniques may be needed in combination with FNAC to diagnose MTC and avoid false negative results.

We present an ultrafast neural network (NN) model, QLKNN, which predicts core tokamak transport heat and particle fluxes. QLKNN is a surrogate model based on a database of 300 million flux calculations of the quasilinear gyrokinetic transport model QuaLiKiz. The database covers a wide range of realistic tokamak core parameters. Physical features such as the existence of a critical gradient for the onset of turbulent transport were integrated into the neural network training methodology. We have coupled QLKNN to the tokamak modelling framework JINTRAC and rapid control-oriented tokamak transport solver RAPTOR. The coupled frameworks are demonstrated and validated through application to three JET shots covering a representative spread of H-mode operating space, predicting turbulent transport of energy and particles in the plasma core. JINTRAC-QLKNN and RAPTOR-QLKNN are able to accurately reproduce JINTRAC-QuaLiKiz T i,e and n e profiles, but 3 to 5 orders of magnitude faster. Simulations which take hours are reduced down to only a few tens of seconds. The discrepancy in the final source-driven predicted profiles between QLKNN and QuaLiKiz is on the order 1%-15%. Also the dynamic behaviour was well captured by QLKNN, with differences of only 4%-10% compared to JINTRAC-QuaLiKiz observed at mid-radius, for a study of density buildup following the L-H transition. Deployment of neural network surrogate models in multi-physics integrated tokamak modelling is a promising route towards enabling accurate and fast tokamak scenario optimization, Uncertainty Quantification, and control applications.

In recent years, endocrine disrupting chemicals have gained interest in human physiopathology and more and more studies aimed to explain how these chemicals compounds affect endocrine system. In human populations, the majority of the studies point toward an association between exposure to endocrine disrupting chemicals and the disorders affecting endocrine axis. A great number of endocrine disrupting chemicals seem to be able to interfere with the physiology of hypothalamus-pituitary-gonadal axis; however, every endocrine axis may be a target for each EDCs and their action is not limited to a single axis or organ. Several compounds may also have a negative impact on energy metabolic homeostasis altering adipose tissue and promoting obesity, metabolic syndrome, and diabetes. Different mechanism have been proposed to explain these associations but their complexity together with the degree of occupational or environmental exposure, the low standardization of the studies, and the presence of confounding factors have prevented to establish causal relationship between the endocrine disorders and exposure to specific toxicants so far. This manuscript aims to review the state of art of scientific literature regarding the effects of endocrine-disrupting chemicals (EDCs) on endocrine system.

Indeterminate neoplasms (IN) represent the gray zone of thyroid cytology in which malignant and benign tumors cannot be discriminated. Recently, the approach by thin core needle biopsy has been proposed. Here we report a new thin core needle biopsy approach in 40 consecutive patients with thyroid IN at cytology. In this study, a 21-G needle was inserted into the nodule, advanced within the lesion, and moved ahead reaching extranodular tissue. The resulting sample allowed to evaluate the cytomorphology of nodular tissue, its relationship with extranodular parenchyma, and the nodule's capsule when present. All biopsies were adequate for diagnosis but one. Of the 39 adequate samples, 5 cases were papillary cancer as confirmed at histology, while 14 nodules avoided surgery because of Hürthle cell hyperplasia in thyroiditis (n = 6) and microfollicular adenomatous hyperplasia (n = 8). The remaining 20 cases were assessed as follicular neoplasms because of encapsulation and were evaluated by immunohistochemistry. Of these, 6 had positive markers in different degree and 1/6 has follicular cancer at histology, while the other 14 were benign after surgery. Overall, this approach by thin core needle biopsy identified benignancy in 14/40 (35 %) IN avoiding surgery. As a conclusion, thin core biopsy should help to discern the nature of thyroid lesions cytologically classified as indeterminate, and it should be used as a complementary test in thyroid nodule assessment.

A power-balance model, with radiation losses from impurities and neutrals, gives a unified description of the density limit (DL) of the stellarator, the L-mode tokamak, and the reversed field pinch (RFP). The model predicts a Sudo-like scaling for the stellarator, a Greenwald-like scaling, , for the RFP and the ohmic tokamak, a mixed scaling, , for the additionally heated L-mode tokamak. In a previous paper (Zanca et al 2017 Nucl. Fusion 57 056010) the model was compared with ohmic tokamak, RFP and stellarator experiments. Here, we address the issue of the DL dependence on heating power in the L-mode tokamak. Experimental data from high-density disrupted L-mode discharges performed at JET, as well as in other machines, are taken as a term of comparison. The model fits the observed maximum densities better than the pure Greenwald limit.

This study shows, as the first in a multicentre series, that FNA-CT sensitivity is higher than that of cytology in diagnosing MTC. To avoid false-negative MTC by cytology, CT measurement in aspiration needle washout is to be performed in all patients undergoing biopsy following high serum CT.