Operator mixing and three-point functions in N=4 SYM

We study the three-point functions between two BPS and one non-BPS local gauge invariant operators in N=4 Super Yang-Mills theory. In particular we show, in explicit 1-loop examples, that the operator mixing discussed in arXiv:0810.0499 plays an important role in the computations of the correlators and is necessary to cancel contributions that would violate the constraints following from the superconformal and the bonus U(1)_Y symmetries. We analyse the same type of correlators also at strong coupling by using the BMN limit of the AdS_5xS^5 string theory. Again the mixing between states with different types of impurities is crucial to ensure the cancellation of various amplitudes that would violate the constraints mentioned above. However, on the string side, we also find some examples of interactions between one non-BPS and two BPS states that do not satisfy expectations based on the superconformal and the bonus U(1)_Y symmetries.Comment: 28 pages, 5 figure

Outcomes of elective liver surgery worldwide: a global, prospective, multicenter, cross-sectional study

Background: The outcomes of liver surgery worldwide remain unknown. The true population-based outcomes are likely different to those vastly reported that reflect the activity of highly specialized academic centers. The aim of this study was to measure the true worldwide practice of liver surgery and associated outcomes by recruiting from centers across the globe. The geographic distribution of liver surgery activity and complexity was also evaluated to further understand variations in outcomes. Methods: LiverGroup.org was an international, prospective, multicenter, cross-sectional study following the Global Surgery Collaborative Snapshot Research approach with a 3-month prospective, consecutive patient enrollment within January–December 2019. Each patient was followed up for 90 days postoperatively. All patients undergoing liver surgery at their respective centers were eligible for study inclusion. Basic demographics, patient and operation characteristics were collected. Morbidity was recorded according to the Clavien–Dindo Classification of Surgical Complications. Country-based and hospital-based data were collected, including the Human Development Index (HDI). (NCT03768141). Results: A total of 2159 patients were included from six continents. Surgery was performed for cancer in 1785 (83%) patients. Of all patients, 912 (42%) experienced a postoperative complication of any severity, while the major complication rate was 16% (341/2159). The overall 90-day mortality rate after liver surgery was 3.8% (82/2,159). The overall failure to rescue rate was 11% (82/ 722) ranging from 5 to 35% among the higher and lower HDI groups, respectively. Conclusions: This is the first to our knowledge global surgery study specifically designed and conducted for specialized liver surgery. The authors identified failure to rescue as a significant potentially modifiable factor for mortality after liver surgery, mostly related to lower Human Development Index countries. Members of the LiverGroup.org network could now work together to develop quality improvement collaboratives

Community detection of seismic point processes

In this paper, we combine robin and Local Indicators of Spatio-Temporal Association (LISTA) functions. robin is an R package to assess the robustness of the community structure of a network found by one or more methods to give indications about their reliability. We use it to propose a classification algorithm of events in a spatio-temporal point pattern, by means of the local second-order characteristics and the community detection procedure in network analysis. We demonstrate the proposed procedure on a real data analysis on seismic data

Community detection analysis with robin on hashtag network

In Social Network science, and especially in the Social Media field, the research of communities is still an open and challenging task, mostly for what concerns the reliability of the results obtained. When dealing with hashtag networks, the research of communities is related to the identification of topics, which is a challenging achievement. Moreover, when dealing with political debates, which is our study’s aim, it is even more complex. In this work, we aim to look for reliable communities on a co-occurrence hashtag network related to the Italian Political campaign (2022). To achieve this goal, we applied two different procedures to compare and validate different community detection algorithms

Exploring the Effect of Individual Characteristics and Social mechanisms on Educational Choices

A large body of researches in both economics and sociology has focused on peer effects in education highlighting as social interactions at primary and secondary levels school affect student outcomes (Coleman et al., 1966; Sacerdote, 2011; Patacchini et al., 2017), aspirations and expectations among adolescents (Raabe and Wölfer, 2019; Lorenz et al., 2020), and secondary school-related choices (Zwier et al., 2023). At university context, peer effects resulting from interactions between students are mainly investigated to explore their effect on academic performance (Winston and Zimmerman, 2004; Griffith and Rask, 2014; Vitale et al., 2016). To the best of our knowledge, studies on university choices have paid little attention to the peer environment (Porcu et al., 2022; Usala et al., 2023 and references therein). Within this study, we examine how individuals’ educational choices in tertiary education dependent on socio-demographic background, the family context, the school environment, and social interactions among peers. Starting from these dimensions, it is important to understand the factors playing a critical role within a perspective where the quality of educational systems can occur only within a scenario of non-reproduction of social inequalities. How and which these contextual effects can interact in the individual choice’s process from high school to university is investigated by data gathered through ad hoc surveys. Data integration procedures are adopted to reconstruct a unique dataset of around 4000 students who have participated to three surveys devoted to a high schools’ sample in Campania region. Hence, logistic regression models are applied to assess the effect of peers and other contextual variables on the probability to enroll at university in a specific disciplinary field as well as on the probability to move in another region to attend a degree program

Dietary Fatty Acids Contribute to Maintaining the Balance between Pro-Inflammatory and Anti-Inflammatory Responses during Pregnancy

Background: During pregnancy, the balance between pro-inflammatory and anti-inflammatory responses is essential for ensuring healthy outcomes. Dietary Fatty acids may modulate inflammation. Methods: We investigated the association between dietary fatty acids as profiled on red blood cells membranes and a few pro- and anti-inflammatory cytokines, including the adipokines leptin and adiponectin at ~38 weeks in 250 healthy women. Results: We found a number of associations, including, but not limited to those of adiponectin with C22:3/C22:4 (coeff -1.44; p = 0.008), C18:1 c13/c14 (coeff 1.4; p = 0.02); endotoxin with C20:1 (coeff -0.9; p = 0.03), C22:0 (coeff -0.4; p = 0.05); MCP-1 with C16:0 (coeff 0.8; p = 0.04); and ICAM-1 with C14:0 (coeff -86.8; p = 0.045). Several cytokines including leptin were associated with maternal body weight (coeff 0.9; p = 2.31 × 10-5), smoking habits (i.e., ICAM-1 coeff 133.3; p = 0.09), or gestational diabetes (i.e., ICAM-1 coeff 688; p = 0.06). Conclusions: In a general cohort of pregnant women, the intake of fatty acids influenced the balance between pro- and anti-inflammatory molecules together with weight gain, smoking habits, and gestational diabetes

VarGenius-HZD allows accurate detection of rare homozygous or hemizygous deletions in targeted sequencing leveraging breadth of coverage

Homozygous deletions (HDs) may be the cause of rare diseases and cancer, and their discovery in targeted sequencing is a challenging task. Different tools have been developed to disentangle HD discovery but a sensitive caller is still lacking. We present VarGenius-HZD, a sensitive and scalable algorithm that leverages breadth-of-coverage for the detection of rare homozygous and hemizygous single-exon deletions (HDs). To assess its effectiveness, we detected both real and synthetic rare HDs in fifty exomes from the 1000 Genomes Project obtaining higher sensitivity in comparison with state-of-the-art algorithms that each missed at least one event. We then applied our tool on targeted sequencing data from patients with Inherited Retinal Dystrophies and solved five cases that still lacked a genetic diagnosis. We provide VarGenius-HZD either stand-alone or integrated within our recently developed software, enabling the automated selection of samples using the internal database. Hence, it could be extremely useful for both diagnostic and research purposes