Effectiveness of the Chebyshev Approximation in Magnetic Field Line Tracking

The tracking of magnetic field lines can be very expensive, in terms of computational burden, when the field sources are numerous and have complex geometries, especially when accuracy is a priority, because an evaluation of the field is required in many situations. In some important applications, the computational cost can be significantly reduced by using a suitable approximation of the field in the integrated regions. This paper shows how Chebyshev polynomials are well-suited for field interpolation in magnetic field-line tracking, then discusses the conditions in which they are most appropriate, and quantifies the effectiveness of parallel computing in the approximation procedures

The risk stratification of adverse neonatal outcomes in women with gestational diabetes (STRONG) study

Aims: To assess the risk of adverse neonatal outcomes in women with gestational diabetes (GDM) by identifying subgroups of women at higher risk to recognize the characteristics most associated with an excess of risk. Methods: Observational, retrospective, multicenter study involving consecutive women with GDM. To identify distinct and homogeneous subgroups of women at a higher risk, the RECursive Partitioning and AMalgamation (RECPAM) method was used. Overall, 2736 pregnancies complicated by GDM were analyzed. The main outcome measure was the occurrence of adverse neonatal outcomes in pregnancies complicated by GDM. Results: Among study participants (median age 36.8 years, pre-gestational BMI 24.8 kg/m2), six miscarriages, one neonatal death, but no maternal death was recorded. The occurrence of the cumulative adverse outcome (OR 2.48, 95% CI 1.59–3.87), large for gestational age (OR 3.99, 95% CI 2.40–6.63), fetal malformation (OR 2.66, 95% CI 1.00–7.18), and respiratory distress (OR 4.33, 95% CI 1.33–14.12) was associated with previous macrosomia. Large for gestational age was also associated with obesity (OR 1.46, 95% CI 1.00–2.15). Small for gestational age was associated with first trimester glucose levels (OR 1.96, 95% CI 1.04–3.69). Neonatal hypoglycemia was associated with overweight (OR 1.52, 95% CI 1.02–2.27) and obesity (OR 1.62, 95% CI 1.04–2.51). The RECPAM analysis identified high-risk subgroups mainly characterized by high pre-pregnancy BMI (OR 1.68, 95% CI 1.21–2.33 for obese; OR 1.38 95% CI 1.03–1.87 for overweight). Conclusions: A deep investigation on the factors associated with adverse neonatal outcomes requires a risk stratification. In particular, great attention must be paid to the prevention and treatment of obesity

Equine maternal aging affects the metabolomic profile of oocytes and follicular cells during different maturation time points

Introduction: Oocyte quality and fertility decline with advanced maternal age. During maturation within the ovarian follicle, the oocyte relies on the associated somatic cells, specifically cumulus and granulosa cells, to acquire essential components for developmental capacity.Methods: A nontargeted metabolomics approach was used to investigate the effects of mare age on different cell types within the dominant, follicular-phase follicle at three time points during maturation. Metabolomic analyses from single oocytes and associated cumulus and granulosa cells allowed correlations of metabolite abundance among cell types.Results and Discussion: Overall, many of the age-related changes in metabolite abundance point to Impaired mitochondrial metabolic function and oxidative stress in oocytes and follicular cells. Supporting findings include a higher abundance of glutamic acid and triglycerides and lower abundance of ceramides in oocytes and somatic follicular cells from old than young mares. Lower abundance of alanine in all follicular cell types from old mares, suggests limited anaerobic energy metabolism. The results also indicate impaired transfer of carbohydrate and free fatty acid substrates from cumulus cells to the oocytes of old mares, potentially related to disruption of transzonal projections between the cell types. The identification of age-associated alterations in the abundance of specific metabolites and their correlations among cells contribute to our understanding of follicular dysfunction with maternal aging

Emerging technologies for the management of Type 1 diabetes in pregnancy

Purpose of Review: The purpose of the study is to discuss emerging technologies available in the management of type 1 diabetes in pregnancy. Recent Findings: The latest evidence suggests that continuous glucose monitoring (CGM) should be offered to all women on intensive insulin therapy in early pregnancy. Studies have additionally demonstrated the ability of CGM to help gain insight into specific glucose profiles as they relate to glycaemic targets and pregnancy outcomes. Despite new studies comparing insulin pump therapy to multiple daily injections, its effectiveness in improving glucose and pregnancy outcomes remains unclear. Sensor-integrated insulin delivery (also called artificial pancreas or closed-loop insulin delivery) in pregnancy has been demonstrated to improve time in target and performs well despite the changing insulin demands of pregnancy. Summary: Emerging technologies show promise in the management of type 1 diabetes in pregnancy; however, research must continue to keep up as technology advances. Further research is needed to clarify the role technology can play in optimising glucose control before and during pregnancy as well as to understand which women are candidates for sensor-integrated insulin delivery

RPC-based Muon Identification System for the neutrino detector of the SHiP experiment

The SHiP experiment has been proposed at CERN to shed light on phenomena still unexplained in the framework of the Standard Model, such as the nature of dark matter, the baryonic asymmetry of the Universe and the neutrino oscillations, searching for hints of New Physics. A section of the detector will be dedicated to the study of neutrino physics with special emphasis on tau neutrino properties, still very poorly measured. A system to identify the muons produced in neutrino interactions, based on RPC technology, has been proposed and it is presented in detail in this paper

DTT - Divertor Tokamak Test facility: A testbed for DEMO

The effective treatment of the heat and power exhaust is a critical issue in the road map to the realization of the fusion energy. In order to provide possible, reliable, well assessed and on-time answers to DEMO, the Divertor Tokamak Test facility (DTT) has been conceived and projected to be carried out and operated within the European strategy in fusion technology. This paper, based on the invited plenary talk at the 31st virtual SOFT Conference 2020, provides an overview of the DTT scientific proposal, which is deeply illustrated in the 2019 DTT Interim Design Report

Observation of Collider Muon Neutrinos with the SND@LHC Experiment

We report the direct observation of muon neutrino interactions with the SND@LHC detector at the Large Hadron Collider. A dataset of proton-proton collisions at √ s = 13.6 TeV collected by SND@LHC in 2022 is used, corresponding to an integrated luminosity of 36.8 fb − 1 . The search is based on information from the active electronic components of the SND@LHC detector, which covers the pseudorapidity region of 7.2 < η < 8.4 , inaccessible to the other experiments at the collider. Muon neutrino candidates are identified through their charged-current interaction topology, with a track propagating through the entire length of the muon detector. After selection cuts, 8 ν μ interaction candidate events remain with an estimated background of 0.086 events, yielding a significance of about 7 standard deviations for the observed ν μ signal