Quantum vacuum effects in non-relativistic quantum field theory

Nonlinearities in the dispersion relations associated with different interactions designs, boundary conditions and the existence of a physical cut-off scale can alter the quantum vacuum energy of a nonrelativistic system nontrivially. As a material realization of this, we consider a 1D-periodic rotating, interacting non-relativistic setup. The quantum vacuum energy of such a system is expected to comprise two contributions: a fluctuation-induced quantum contribution and a repulsive centrifugal-like term. We analyze the problem in detail within a complex Schoedinger quantum field theory with a quartic interaction potential and perform the calculations non-perturbatively in the interaction strength by exploiting the nonlinear structure of the associated nonlinear Schroedinger equation. Calculations are done in both zeta-regularization, as well as by introducing a cut-off scale. We find a generic, regularization-independent behavior, where the competition between the interaction and rotation can be balanced at some critical ring-size, where the quantum vacuum energy has a maxima and the force changes sign. The inclusion of a cut-off smoothes out the vacuum energy at small distance but leaves unaltered the long distance behavior. We discuss how this behavior can be tested with ultracold-atoms.Comment: 10 pages, 3 figure

Self-Supervised Music Source Separation Using Vector-Quantized Source Category Estimates

Music source separation is focused on extracting distinct sonic elements from composite tracks. Historically, many methods have been grounded in supervised learning, necessitating labeled data, which is occasionally constrained in its diversity. More recent methods have delved into N-shot techniques that utilize one or more audio samples to aid in the separation. However, a challenge with some of these methods is the necessity for an audio query during inference, making them less suited for genres with varied timbres and effects. This paper offers a proof-of-concept for a self-supervised music source separation system that eliminates the need for audio queries at inference time. In the training phase, while it adopts a query-based approach, we introduce a modification by substituting the continuous embedding of query audios with Vector Quantized (VQ) representations. Trained end-to-end with up to N classes as determined by the VQ's codebook size, the model seeks to effectively categorise instrument classes. During inference, the input is partitioned into N sources, with some potentially left unutilized based on the mix's instrument makeup. This methodology suggests an alternative avenue for considering source separation across diverse music genres. We provide examples and additional results online.Comment: 4 pages, 2 figures, 1 table; Accepted at the 37th Conference on Neural Information Processing Systems (2023), Machine Learning for Audio Worksho

Remote Working and Mental Health during the First Wave of COVID-19 Pandemic

We use longitudinal data from the SHARE survey to estimate the causal effect of remote working during the COVID-19 pandemic on mental health of senior Europeans. We face endogeneity concerns both for the probability of being employed during the pandemic and for the choice of different work arrangements conditional on employment. Our research design overcomes these issues by exploiting variation in the technical feasibility of remote working across occupations and in the legal restrictions to in-presence work across sectors. We estimate heterogeneous effects of remote working on mental health: we find negative effects for respondents with children at home and for those living in countries with low restrictions or low excess death rates due to the pandemic. On the other hand, the effect is positive for men and for respondents with no co-residing children

Clarifying the Roles of Greenhouse Gases and ENSO in Recent Global Warming through Their Prediction Performance

Abstract It is well known that natural external forcings and decadal-to-millennial variability drove changes in the climate system throughout the Holocene. Regarding recent times, attribution studies have shown that greenhouse gases (GHGs) determined the trend of temperature (T) in the last half century, while circulation patterns contributed to modify its interannual, decadal, or multidecadal behavior over this period. Here temperature predictions based on vector autoregressive models (VARs) have been used to study the influence of GHGs and El Niño–Southern Oscillation (ENSO) on recent temperature behavior. It is found that in the last decades of steep temperature increase, ENSO shows just a very short-range influence on T, while GHGs are dominant for each forecast horizon. Conversely and quite surprisingly, in the previous quasi-stationary period the influences of GHGs and ENSO are comparable, even at longer range. Therefore, if the recent hiatus in global temperatures should persist into the near future, an enhancement of the role of ENSO can be expected. Finally, the predictive ability of GHGs is more evident in the Southern Hemisphere, where the temperature series is smoother

Potentiality of protein fractions from the house cricket (Acheta domesticus) and yellow mealworm (Tenebrio molitor) for pasta formulation

House cricket (Acheta domesticus; AD) and yellow mealworm (Tenebrio molitor; TM) are two promising insect species for possible novel food applications. In this research the insect protein fractions were extracted, characterised, and used in the manufacturing of pasta by replacing semolina with 14% of powdered proteins. Pasta samples were then analysed to evaluate technological quality aspects. Results showed that insect protein inclusion resulted in a darker (L* value: 76.7, 53.4, 59.9 for control, AD and TM, respectively) and firmer (12.4, 13.7, 13.8 N: control, AD and TM, respectively) AD and TM pasta, and a higher water absorption index for AD (148, 178, 150%: control, AD and TM, respectively). In conclusion, both extracts offer interesting opportunity for pasta formulations, possibly leading to an improved protein content and quality. From an industrial perspective, the present study demonstrated that the tested edible insects can provide protein extracts for the possible fortification of pasta with high-quality protein and technological traits, thus representing an ingredient with interesting potential for several food applications

Crystal structure analyses facilitate understanding of synthesis protocols in the preparation of 6,6′-dibromo-substituted BINOL compounds

A combination of crystallographic and spectroscopic techniques has been used in order to address thorough purification protocols for a series of atropisomeric 1,1′-binaphthalene-2,2′-diol (BINOL) derivatives to be used as building blocks for chiral nanoscale constructs

Chiral nanostructuring of multivalent macrocycles in solution and on surfaces

We describe the design and synthesis of a novel functionality-rich, homochiral macrocycle, possessing the overall molecular D-2 symmetry, in which multivalency is introduced into the covalent framework by means of four suitably positioned pyridine moieties. The macrocycle synthesis is carried out with functionalized, enantiopure 1,1'-binaphthyl synthons as the source of chirality by means of a room temperature esterification reaction as the cyclization procedure. Upon addition of Pd2+, coordination of the pyridine moieties occurs both intra and intermolecularly, to afford chiral ordered mono and dimeric macrocycles or multimeric aggregates depending on the solvents and conditions used. The metal binding event takes place in combination with a significant macrocyclic conformational rearrangement detected by circular dichroism spectroscopy. When in combination with a third component (C-60), the macrocycle-Pd2+ hybrid undergoes surface-confined nanostructuring into chiral nanofibres