Search

We investigate medium-energy angular distributions data of proton elastic scattering on $^{12}$C, with the aim to probe the existence of cluster distributions in the ground state of $^{12}$C. In our approach, we exploit Coupled-Channel calculations to describe the scattering from a spheroidal-like structure, and we include a further contribution, based on a diffraction scattering formula, to explicitly take into account a possible triangular $\alpha$-cluster structure of the target. From the present analysis, we find a quite small cluster component in $^{12}$C ground state (with an upper limit on the occurrence probability of $1\%$, $99.75\%$ confidence level) and an inter-cluster distance of $\simeq 3.9$ fm. These values are compared with several theoretical predictions reported in the literature.

The presence of surface layers with altered chemical composition in gold alloys is investigated exploiting X-ray line ratios populated in energy-dispersive X-ray fluorescence investigations. We show that the use of the Ag (Lα/Kα) X-ray ratio and the Ag (Lα/Kα)/Au (Mα/Lα) double-ratio allows to ascertain surface gold enrichment that can be attributed to a depletion of silver concentration in a thin (

We perform a comprehensive analysis of complete fusion cross section data with the aim to derive, in a completely data-driven way, a model suitable to predict the integrated cross section of the fusion between light-to-medium mass nuclei at above barrier energies. To this end, we adopted a novel artificial intelligence approach, based on a hybridization of genetic programming and artificial neural networks, capable to derive an analytical model for the description of experimental data. The approach enables to perform a global search for computationally simple models over several variables and a considerable body of nuclear data. The derived phenomenological formula can serve to reproduce the trend of fusion cross section for a large variety of light to intermediate mass collision systems in an energy domain ranging approximately from the Coulomb barrier to the onset of multi-fragmentation phenomena.

In this paper, we report a detailed study on the de-excitation of the 46Ti compound nucleus populated by means of four different reactions: 16O + 30Si at 7 and 8 AMeV, 18O + 28Si at 7 AMeV and 19F + 27Al at 7 AMeV. The GARFIELD detection array was used to measure the light charged particles and the heavy fragments emitted. This setup covers a large fraction of the solid angle with high-granularity. Complete events are chosen through total charge (Z TOT = 22) detection. Fusion-evaporation events are selected based on the condition that only one heavy fragment is detected in coincidence with the light charged particles. The analysis of global observables, such as charge distribution and light charged particle multiplicities, is compatible with the formation of a thermalized compound nucleus for all the four reactions. Nevertheless, an enhanced emission of α-particles with respect to a pure statistical picture is observed at very forward angles (α-particles.

Aims The effective identification of individuals with early dysglycemia status is key to reduce the incidence of type 2 diabetes. We develop and validate a novel zero-cost tool that significantly simplifies the screening of undiagnosed dysglycemia. Methods We use NHANES cross-sectional data over 10 years (2007–2016) to derive an equation that links non-laboratory exposure variables to the possible presence of undetected dysglycemia. For the first time, we adopt a novel artificial intelligence approach based on the Darwinian evolutionary theory to analyze health data. We collected data for 47 variables. Results Age and waist circumference are the only variables required to use the model. To identify undetected dysglycemia, we obtain an area under the curve (AUC) of 75.3%. Sensitivity and specificity are 0.65 and 0.73 by using the optimal threshold value determined from external validation data. Conclusions The use of uniquely two variables allows to obtain a zero-cost screening tool of analogous precision than that of more complex tools widely adopted in the literature. The newly developed tool has clinical use as it significantly simplifies the screening of dysglycemia. Furthermore, we suggest that the definition of an age-related waist circumference cut-off might help to improve existing diabetes risk factors.

This paper presents an automatic method for data classification in nuclear physics experiments based on evolutionary computing and vector quantization. The major novelties of our approach are the fully automatic mechanism and the use of analytical models to provide physics constraints, yielding to a fast and physically reliable classification with nearly-zero human supervision. Our method is successfully validated using experimental data produced by stacks of semiconducting detectors. The resulting classification is highly satisfactory for all explored cases and is particularly robust to noise. The algorithm is suitable to be integrated in the online and offline analysis software of existing large complexity detection arrays for the study of nucleus–nucleus collisions at low and intermediate energies.

Aims: We perform a stratified analysis of the recently published age-related waist circumference cut-off model to validate its performance in the screening of dysglycemia in the US population. Methods: We use NHANES data as representative of the US population. Data were subdivided into sex, ethnic and glycemia groups. We evaluate the performance of the model separately in each group through the AUC. We also discuss the calibration of the model. Results: For the sex-stratified analysis, we obtain AUC = 0.69–0.71 (95% C.I.) for male individuals and AUC = 0.75–0.78 (95% C.I.) for female individuals. The stratified analysis is performed in different ethnic groups, namely “Mexican American”, “Other Hispanic”, “Non-Hispanic White”, “Non-Hispanic Black” and “Other Race – Including Multi-Racial. We obtain, respectively, AUC = 0.74–0.75, AUC = 0.76–0.78, AUC = 0.73–0.75, AUC = 0.74–0.77 and AUC = 0.71–0.73 (95% C.I.). The model achieves AUC = 0.70–0.73 (95% C.I.) in the identification of individuals with prediabetes and AUC = 0.70–0.80 (95% C.I.) in the identification of individuals with diabetes. Conclusions: The accuracy of the model turns out to be similar in each group considered in the stratified analysis, indicating that the model is suitable to be used as a screening tool for dysglycemia in the US population.

A new study of the quasi-free contribution to the $$^3\hbox {He}+\,^9\hbox {Be}\rightarrow 3\alpha $$ reaction (Q value = 19.004 MeV) at low $${E}_{^3{{\mathrm{He}}}}$$ energy is presented. The reaction was studied in a kinematically complete experiment at beam energy of 4 MeV. To clarify the presence of the quasi-free mechanism, the $$^4{\hbox {He}}$$–$$^5\hbox {He}$$ momentum distribution of the $$^9\hbox {Be}$$ ground state was extracted. Standard tests were also carried out to confirm the presence of the quasi-free contribution and are reported in this work. The full width at half maximum of the $$^4\hbox {He}$$–$$^5\hbox {He}$$ inter-cluster momentum distribution inside $$^9\hbox {Be}$$ was measured with improved accuracy, by adopting several different approaches that all led to consistent results. These preliminary investigations on the reaction mechanism are fundamental for future studies employing the Trojan Horse Method, with the $$^5\hbox {He}$$ unbound nucleus as a virtual projectile.

Background: Type 2 diabetes is a major risk factor for death. It currently affects about 26.8 million people in the US population and its prevalence is increasing. In this framework, the effective identification of individuals with early dysglycemia status is a crucial task for the national health system, as one of the primary diabetes prevention methods. To this end, developing practical tools for large-scale screenings of dysglycemia at zero-cost is key. Methods: We use NHANES cross-sectional data over 10 years (2007-2016) to derive an equation that links non-laboratory exposure variables to the possible presence of undetected dysglycemia. For the first time, we adopt a novel artificial intelligence approach based on the Darwinian evolutionary theory to analyze health data. In our approach, the optimal model to identify dyglycemia and the variables to exploit are obtained through a sort of natural selection process simulated via genetic programming. We collected data for 47 variables, previously suggested in the literature as good non-laboratory predictors for dysglycemia, including age, gender, waist circumference, ethnic group of belonging, hypertension, BMI and family history of high blood glucose. Individuals with dysglycemia included both prediabetic and undetected type 2 diabetic. Individuals with gestational diabetes, type 1 diabetes or diagnosed type 2 diabetes were excluded from our analysis. Large care was devoted in obtaining a dataset with the analogous prevalence, in each age group and gender, as in the US national population. Our model is derived using data for 9034 individuals and is validated internally and also via cross-sectional data that were not used to derive the equation. Findings: We develop a novel screening tool to detect the possible presence of dysglycemia based on a simple mathematical equation that exploits only two variables: age and waist circumference. We obtain an Area Under the Curve (AUC) of 75.3% (74.0%-76.7%, 95% C.I.) based on the analysis of 4581 individuals used for internal validation. Sensitivity and specificity are 0.65 (0.63 - 0.66, 95% C.I.) and 0.73 (0.71 - 0.75, 95% C.I.), respectively, by using the optimal threshold value determined from external validation data. Using a threshold optimized for high-sensitivity values, we obtain sensitivity 0.82 (0.80 - 0.83, 95% C.I.) and specificity 0.53 (0.50 - 0.55, 95% C.I.). Interpretation: We show that the use of uniquely two variables allows to obtain a zero-cost screening tool of analogous precision than that of more complex tools widely adopted in the literature. Furthermore, we suggest that the definition of an age-related waist circumference cut-off might crucially help in the identification of individuals with undetected dysglycemia. The underlying result indicates that the introduction of concepts derived from the Darwinian evolutionary theory in the analysis of health data could enable to a larger discovery potential compared to more conventional analysis methods previously applied in the literature. Funding Statement: None. Declaration of Interests: None.

The study of the emitted particles, comparing pre-equilibrium and thermal components, is a useful tool to examine the nuclear structure of emitters. Possible clustering effects, which may change the expected decay chain probability, could be highlighted on the competition between different reaction mechanisms. The NUCL-EX collaboration (INFN, Italy) has carried out an extensive research campaign on pre-equilibrium emission of light charged particles from hot nuclei. In this framework, the reactions 16O+30Si, 18O+28Si, 19F+27Al at 7 AMeV and 16O+30Si at 8 AMeV have been carried out using the GARFIELD+RCo array at Legnaro National Laboratories. Some anomalies in the α-particle emission channels have been evidenced in the measurement reported above, showing in an exclusive way the observed effects related to the entrance channels. The experimental results are compared to model prediction, for which the same filtering and complete event selection have been applied.

The 32S(3He,d)33Cl one-proton transfer reaction is a powerful tool to investigate the spectroscopy of low-lying states in the proton-rich 33Cl nucleus. However, the extraction of firm differential cross-section data at various angles to benchmark and constrain theoretical models is made challenging by the presence of competitive reactions on target contaminants. In this paper we report on a recent measurement using a new generation hodoscope of silicon detectors, capable to detect and identify emitted deuterons down to energies of the order of 2 MeV. The high angular segmentation of our hodoscope combined with a suitable target to control possible contaminants, allowed to unambiguously disentangle the contribution of various states in 33Cl, in particular the 2.352 MeV state lying just few tens of keV above the proton separation energy.

International audience; A useful tool to underline possible structure effects on the competition between different reaction mechanisms, which may change the expected decay chain probability, is the exclusive study of light charged particles emission from hot light composite systems. In particular, the influence of projectile structure may be evidenced by studying the competition between fast and thermal emissions. In this framework, the four reactions ^16O+^30Si, ^18O+^28Si, ^19F+^27Al at 7 MeV/u and ^16O+^30Si at 8 MeV/u have been carried out using the GARFIELD+RCo array at Legnaro National Laboratories. Some anomalies in the α-particle emission channels have been evidenced in the measurements reported above, showing in an exclusive way the observed effects related to the entrance channels. The experimental results are compared to statistical model predictions, for which the same filtering and complete event selection have been applied.

We have derived a new thermonuclear rate with an associated uncertainty for the 10B(α, p)13C reaction by evaluating the available experimental data for the first time. We provide this rate with a much smaller uncertainty than that estimated in the literature. Our rate differs significantly from the theoretical rates adopted in the current reaction rate libraries. Utilizing this new rate, we have investigated its astrophysical implications on the heavy-element (especially, p-nuclei) production in the νp- process in a stellar model of the neutrino-driven wind of type II core-collapse supernova. It shows that our rate with a much smaller uncertainty strongly constrains the nucleosynthetic results of the light p-nulcei with A ∼ 80-100. In addition, it shows that the difference between observed and predicted abundances for light p- nuclei is quite large, implying either that the present stellar model still needs modification or that additional astrophysical sources are required to account for the origin of some p- nuclei, such as 92Mo and 94Mo.

Proper selection of the quasi-free (QF) break-up channel in a three-body reaction is a key aspect for the applicability of the Trojan Horse Method (THM). The Treiman-Yang (TY) Criterion is a model-independent experimental test for the dominance of the QF mechanism, and hence constitutes one of the strongest validity tests of the THM. An experiment was performed at LNS to apply the test to the d(10B, 7Be α)n reaction. Here, the criterion is described and some preliminary data from the experiment are shown.

The spectroscopy of 13 C excited states above the alpha emission threshold has been investigated by studying data on 9 Be(α,α )9 Be and 9 Be(α ,n)12 C collisions at bombarding energies in the range Eα ≈2-10 MeV. A multichannel R -matrix fit allowed us to better constrain the spectroscopy of 13 C states above the α threshold (10.65 MeV). Preliminary results on this analysis will be discussed.

The study of nuclear cluster states bound by valence neutrons is a field of recent large interest. In particular, it is interesting to study the pre-formation of α-clusters in α-conjugate nuclei and the dynamical condensation of clusters during nuclear reactions. The NUCL-EX collaboration (INFN, Italy) is carrying out a research campaign studying preequilibrium emission of light charged particles and cluster properties of light and medium mass nuclei. For this purpose, a comparative study of the three nuclear reactions: O 16 + Si 30 , O 18 + Si 28 and F 19 + 27Al, has been recently carried out using the GARFIELD+RCo 4π setup. After a general introduction on the experimental campaign, the preliminary results for the three systems are presented.

International audience; The FAZIA apparatus exploits Pulse Shape Analysis (PSA) to identify nuclear fragments stopped in the first layer of a Silicon-Silicon-CsI(Tl) detector telescope. In this work, for the first time, we show that the isotopes of fragments having atomic number as high as Z∼20 can be identified. Such a remarkable result has been obtained thanks to a careful construction of the Si detectors and to the use of low noise and high performance digitizing electronics. Moreover, optimized PSA algorithms are needed. This work deals with the choice of the best algorithm for PSA of current signals. A smoothing spline algorithm is demonstrated to give optimal results without requiring too much computational resources.

International audience; The study of nuclear cluster states bound by valence neutrons is a field of recent large interest. In particular, it is important to study the pre-formation of α-clusters in α-conjugate nuclei and the dynamical condensation of clusters during nuclear reactions [1–5]. The NUCL–EX collaboration has recently initiated an experimental campaign of exclusive measurements of fusion–evaporation reactions with light nuclei as interacting partners. In collisions involving light systems, the low expected multiplicity of fragments increases the probability of achieving a quasi-complete reconstruction of the event. In particular the formation and decay modes of an excited 24Mg system have been studied through two different reactions, 12C (95 MeV)+ 12C and 14N (80.7 MeV)+ 10B, which have been used to produce fused systems with nearly the same mass and excitation energy (~60 MeV). In particular, even the de-excitation of the Hoyle state in 12C have been studied, both in peripheral (projectiles de-excitation) and in central collisions (six α-particles channel). Moreover, a research campaign studying pre-equilibrium emission of light charged particles and cluster properties of light and medium-mass nuclei has been carried out. For this purpose, a comparative study of the three nuclear systems 18O+28Si, 16O+30Si and 19F+27Al has been recently studied using the GARFIELD+RCo 4π setup [6]. The experimental data are compared with the predictions of simulated events generated with the statistical models (GEMINI++ and HFl) and through dynamical models like Stochastic Mean Field (SMF) and Antisymmetrized Molecular Dynamics (AMD) and filtered with a software replica of our apparatus in order to take into account the experimental conditions.

The 10 B(p,α )7 Be reaction is the main responsible for the 10 B destruction in stellar interior [1]. In such environments this p-capture process occurs at a Gamow energy of 10 keV and takes places mainly through a resonant state (Ex = 8.701 MeV) of the compound 11 C nucleus. Thus a resonance right in the region of the Gamow peak is expected to significantly influence the behavior of the astrophysical S(E)-factor. The 10 B(p,α )7 Be reaction was studied via the Trojan Horse Method (THM) applied to the 2 H(10 B,α 7 Be)n in order to extract the astrophysical S(E)-factor in a wide energy range from 5 keV to 1.5 MeV.

We report preliminary results of a new measurement of the 10 B(p,α 0 )7 Be cross section in the 0.6 - 1.0 MeV bombarding energy domain. In this region very few data have been reported in the literature. Excitation functions at both forward and backward angles have been obtained. Angular distributions testify the contribution due to several excited states in the 11 C compound nucleus. The experimental S -factor is about 30% lower than the one reported in the literature and based on activation methods.

International audience; The experimental investigation of Heavy Ion reactions at Fermi energies requires an accurate measurement of observables, such as linear momentum and energy of the detected particles. In order to address this problem, dedicated and flexible correlator arrays are useful tools to be coupled with 4pi detectors. One of these arrays is FARCOS, presently under construction at the INFN Sezione di Catania and Laboratori Nazionali del Sud (LNS).

We discuss new results concerning the investigation of the 19F(p, α 0)16O and 10B(p, α 0)7Be reactions at low energies. Both reactions are important for the nuclear spectroscopy of the formed compound nucleus, i.e. 20Ne and 11C respectively, and play a role in nuclear astrophysics. For the 10B(p, α 0)7Be case, a comprehensive analysis of our reaction data and other scattering data points out the possible presence of an unreported state in 11C at Ex ≈ 9.36 MeV. For the 19F(p, α 0)16O case, the study of the low energy angular distributions testifies the role played by low energy resonances in the S-factor, leading to an enhanced reaction rate at stellar energies.

The thermonuclear 19F(p, )16O reaction rate in the temperature region 0.007–10 GK has been derived by re-evaluating the available experimental data, together with the low-energy theoretical R-matrix extrapolations. Our new rate deviates by up to about 30% compared to the previous results, although all rates are consistent within the uncertainties. At very low temperature (e.g. 0.01 GK) our reaction rate is about 20% lower than the most recently published rate, because of a difference in the low energy extrapolated S-factor and a more accurate estimate of the reduced mass used in the calculation of the reaction rate. At temperatures above ~1 GK, our rate is lower, for instance, by about 20% around 1.75 GK, because we have re-evaluated the previous data (Isoya et al., Nucl. Phys. 7, 116 (1958)) in a meticulous way. The present interpretation is supported by the direct experimental data. The uncertainties of the present evaluated rate are estimated to be about 20% in the temperature region below 0.2 GK, and are mainly caused by the lack of low-energy experimental data and the large uncertainties in the existing data. Asymptotic giant branch (AGB) stars evolve at temperatures below 0.2 GK, where the 19F(p, )16O reaction may play a very important role. However, the current accuracy of the reaction rate is insufficient to help to describe, in a careful way, the fluorine over-abundances observed in AGB stars. Precise cross section (or S factor) data in the low energy region are therefore needed for astrophysical nucleosynthesis studies.