Constraining relativistic models through heavy ion collisions

Relativistic models can be successfully applied to the description of compact star properties in nuclear astrophysics as well as to nuclear matter and finite nuclei properties, these studies taking place at low and moderate temperatures. Nevertheless, all results are model dependent and so far it is unclear whether some of them should be discarded. Moreover, in the regime of hot hadronic matter very few calculations exist using these relativistic models, in particular when applied to particle yields in heavy ion collisions. In the present work we comment on the known constraints that can help the selection of adequate models in this regime and investigate the main differences that arise when the particle production during a Au+Au collision at RHIC is calculated with different models.Comment: 9 pages, 1 figure, 3 table

Magnetorotational supernovae: a nucleosynthetic analysis of sophisticated 3D models

Magnetorotational supernovae are a rare type of core-collapse supernovae where the magnetic field and rotation play a central role in the dynamics of the explosion. We present the post-processed nucleosynthesis of state-of-the-art neutrino-MHD supernova models that follow the post explosion evolution for few seconds. We find three different dynamical mechanisms to produce heavy r-process elements: (i) a prompt ejection of matter right after core bounce, (ii) neutron-rich matter that is ejected at late times due to a reconfiguration of the protoneutronstar shape, (iii) small amount of mass ejected with high entropies in the centre of the jet. We investigate total ejecta yields, including the ones of unstable nuclei such as 26Al, 44Ti, 56Ni, and 60Fe. The obtained 56Ni masses vary between 0.01−1M⊙⁠. The latter maximum is compatible with hypernova observations. Furthermore, all of our models synthesize Zn masses in agreement with observations of old metal-poor stars. We calculate simplified light curves to investigate whether our models can be candidates for superluminous supernovae. The peak luminosities obtained from taking into account only nuclear heating reach up to a few ∼1043ergs−1⁠. Under certain conditions, we find a significant impact of the 66Ni decay chain that can raise the peak luminosity up to ∼38 percent compared to models including only the 56Ni decay chain. This work reinforces the theoretical evidence on the critical role of magnetorotational supernovae to understand the occurrence of hypernovae, superluminous supernovae, and the synthesis of heavy elements

Mechanism of tribo-chemical reactions of ionic liquids on titanium alloys

In this paper, the tribological, the tribo-chemical reaction mechanisms and desorption properties of three ionic liquids (ILs), [Bu3MeP][ Tf2N], [Bu3MeN][ Tf2N] and [Bu3MeP][ (MeO)2PO2], in contact with titanium and under vacuum conditions are studied with the CATRI © UHV Tribometer developed by IK4-TEKNIKER [1]. The two ILs containing the bis(trifluoromethanesulfonyl)amide anion presented lower coefficient of friction compared to that having the dimethyl phosphate anion. The tribodesorption study revealed that it is required an induction period to decrease the friction coefficient. The end of this period is accelerated in the case of trifluoromethane ionic liquids by the CF3+ release. Hence, the CF3+ reacts with the titanium surface generating a titanium fluoride tribolayer that could act like a catalyst to generate the tribodesorption of ionic liquid cation fragments (CH3+, C2H5+, C3H7+, C4H9+). The XPS analysis confirmed the generation of a boundary film, comprising of sulfide and inorganic fluoride, and being possibly the responsible of decreasing the friction coefficient. The [Bu3MeP][MeO)2PO2] ionic liquid required a long induction period, it did not form any tribolayer and no reduction of friction coefficient, yielding instead a high abrasion and adhesion mechanism. Thus, it can be concluded that bis(trifluoromethanesulfonyl)amide anion is more effective than dimethylphosphate in generating a surface protective film on the titanium surface under the selected test conditions and the testing methodology seems to be useful to understand the tribodesorption mechanism.The partners would like to acknowledge the financing to the Austrian Government financing of COMET K2 Excellence Centre of Tribology called X-Tribology to carry out this research collaborative activity. The authors also would like to acknowledge the financing of the EMAITEK Programme by the Basque Country

How has selection for residual feed intake (RFI) affected the grow-finish pig’s ability to cope with stress?

Feed is the largest cost in pork production; therefore, improving feed efficiency can increase producer profitability. Furthermore improved feed efficiency can support industry competitiveness, decrease the demand on global feed resources, and complement environmental sustainability. Genetically, selective breeding for residual feed intake (RFI) shows promise in meeting these increased demands. However, it is important to balance the benefits of feed efficiency selection with the pig’s ability to cope with stress and its welfare. Therefore, this factsheet will discuss physiological and behavioral stress research on swine selected on the basis of RFI

Improved nutrient digestibility and retention partially explains feed efficiency gains in pigs selected for low residual feed intake

Residual feed intake (RFI) is a unique measure of feed efficiency (FE) and an alternative to traditional measures. The RFI is defined as the difference between the actual feed intake of a pig and its expected feed intake based on a given amount of growth and backfat. Therefore, selecting pigs with a low RFI (LRFI) results in a more feed-efficient animal for a given rate of growth. Our objective was to determine the extent to which apparent total tract digestibility of nutrients and energy use and retention may explain FE differences between pigs divergently selected for LRFI or high RFI (HRFI). After 7 generations of selection, 12 HRFI and 12 LRFI pigs (62 ± 3 kg BW) were randomly assigned to metabolism crates. Pigs had free access to a standard diet based on corn (Zea mays) and soybean (Glycine max) meal containing 0.4% TiO2, an exogenous digestibility marker. After a 7-d acclimation, total urine and feces were collected for 72 h. Nutrient and energy digestibility, P digestibility, and N balance were then measured and calculated to determine differences between the RFI lines. As expected, ADFI was lower (2.0 vs. 2.6 kg; P \u3c 0.01), ADG did not differ, and FE was higher in the LRFI (P \u3c 0.001) compared to the HRFI pigs. The digestibility values for DM (87.3 vs. 85.9%), N (88.3 vs. 86.1%), and GE (86.9 vs. 85.4%) were higher (P ≤ 0.003) in the LRFI vs. HRFI pigs, respectively. The DE (16.59 vs. 16.32 MJ/kg DM) and ME (15.98 vs. 15.72 MJ/kg DM) values were also greater (P \u3c 0.001) in LRFI pigs. When correcting for ADFI, P digestibility did not differ between the lines. However, the LRFI pigs tended to have improved N retention (P = 0.08) compared to HRFI pigs (36.9 vs. 32.1 g/d). In conclusion, the higher energy and nutrient digestibility, use, and retention may partially explain the superior FE seen in pigs selected for LRFI

Magnetorotational supernovae: a nucleosynthetic analysis of sophisticated 3D models

Magnetorotational supernovae are a rare type of core-collapse supernovae where the magnetic field and rotation play a central role in the dynamics of the explosion. We present the post-processed nucleosynthesis of state-of-the-art neutrino-MHD supernova models that follow the post explosion evolution for few seconds. We find three different dynamical mechanisms to produce heavy r-process elements: (i) a prompt ejection of matter right after core bounce, (ii) neutron-rich matter that is ejected at late times due to a reconfiguration of the protoneutronstar shape, (iii) small amount of mass ejected with high entropies in the centre of the jet. We investigate total ejecta yields, including the ones of unstable nuclei such as 26Al, 44Ti, 56Ni, and 60Fe. The obtained 56Ni masses vary between 0.01−1M⊙. The latter maximum is compatible with hypernova observations. Furthermore, all of our models synthesize Zn masses in agreement with observations of old metal-poor stars. We calculate simplified light curves to investigate whether our models can be candidates for superluminous supernovae. The peak luminosities obtained from taking into account only nuclear heating reach up to a few ∼1043ergs−1. Under certain conditions, we find a significant impact of the 66Ni decay chain that can raise the peak luminosity up to ∼38 percent compared to models including only the 56Ni decay chain. This work reinforces the theoretical evidence on the critical role of magnetorotational supernovae to understand the occurrence of hypernovae, superluminous supernovae, and the synthesis of heavy elements

Protein sequence analysis using the MPI Bioinformatics Toolkit

The MPI Bioinformatics Toolkit (https://toolkit.tuebingen.mpg.de) provides interactive access to a wide range of the best‐performing bioinformatics tools and databases, including the state‐of‐the‐art protein sequence comparison methods HHblits and HHpred. The Toolkit currently includes 35 external and in‐house tools, covering functionalities such as sequence similarity searching, prediction of sequence features, and sequence classification. Due to this breadth of functionality, the tight interconnection of its constituent tools, and its ease of use, the Toolkit has become an important resource for biomedical research and for teaching protein sequence analysis to students in the life sciences. In this article, we provide detailed information on utilizing the three most widely accessed tools within the Toolkit: HHpred for the detection of homologs, HHpred in conjunction with MODELLER for structure prediction and homology modeling, and CLANS for the visualization of relationships in large sequence datasets. Basic Protocol 1: Sequence similarity searching using HHpred Alternate Protocol: Pairwise sequence comparison using HHpred Support Protocol: Building a custom multiple sequence alignment using PSI‐BLAST and forwarding it as input to HHpred Basic Protocol 2: Calculation of homology models using HHpred and MODELLER Basic Protocol 3: Cluster analysis using CLAN