Machine Learning techniques applied to the statistical properties of spin systems

In recent years Machine Learning has proved to be successful in many technological applications and scientific tasks, such as image and speech recognition, natural language understanding and more. In this work we apply both supervised and unsupervised Machine Learning to three key problems in statistical physics: design of Hamiltonian from data, phase recognition and study of critical properties of a system undergoing phase transition. As an example of model design, we use a dataset with spin configurations and corresponding energies randomly sampled from a one dimensional Ising model. We then make two guesses for the correct Hamiltonian: the former involving interactions of spins with an external local field, the latter involving two body interactions among spins. The coupling constants are determined with a linear penalized regression, comparing the effects of L1 and L2 penalization terms of the cost function. We pay specific attention to the problem of overfitting and to the validation process, which is critical for accepting or rejecting the proposed model. The phase recognition problem is faced with the two dimensional Ising and XY models as examples. After showing the limits of a simple softmax regression for this task, we build suitable neural networks to overcome these limits. In particular, a feed forward network is built and the learning process is investigated for the Ising model; while a more sophisticated convolutional network is proposed for the XY model in order to detect local topological structures. The last part of the work is dedicated to the unsupervised study of phase transitions, and the determination of critical properties (order parameter, critical temperature, critical exponents). The discussed techniques are Principal Component Analysis (PCA) for dimensional reduction and K-means clustering for organizing data into subsets with specific properties. PCA is applied to the two dimensional Ising, Potts and XY models, and it is used to find suitable order parameters. The study of the proposed order parameter as a function of temperature provides evidence of phase transition, and a finite size scaling allows to extrapolate both the critical temperature in the thermodynamic limit, and the $\nu$ critical exponent for the correlation length. K-means clustering is applied to equilibrium configurations of the two dimensional Ising model, before and after the dimensional reduction, and the critical temperature is estimated. Moreover, a clustering of relaxation curves of magnetization in a Monte Carlo dynamics is used to build a phase diagram on the parameter space of temperature and magnetic field. A synergy of C++, Python and Wolfram Mathematica 12.0 is used throughout this work in order to sample input datasets and to build and control customized neural networks and learning tools. The most relevant codes are provided in the appendix.ope

Casein phosphopeptides : from milk to nutraceutical

Milk and dairy products are known sources of bioavailable calcium for its association with casein, whose proteolysis produces caseinphosphopeptides (CPPs). CPPs are phosphorylated peptides able to bind and solubilise calcium. In human intestinal tumor cells differentiated in vitro toward an enterocityc phenotype, they also induce a calcium uptake. Moreover, in human in vitro osteoblasts, CPPs favour the mineralization of the extracellular matrix. CPPs can differently affect proliferation and apoptosis in differentiated and /or tumor intestinal cells. Due to all these properties, CPPs may be considered as potential nutraceutical/functional food

Simulation-based Fault Injection with QEMU for Speeding-up Dependability Analysis of Embedded Software

Simulation-based fault injection (SFI) represents a valuable solu- tion for early analysis of software dependability and fault tolerance properties before the physical prototype of the target platform is available. Some SFI approaches base the fault injection strategy on cycle-accurate models imple- mented by means of Hardware Description Languages (HDLs). However, cycle- accurate simulation has revealed to be too time-consuming when the objective is to emulate the effect of soft errors on complex microprocessors. To overcome this issue, SFI solutions based on virtual prototypes of the target platform has started to be proposed. However, current approaches still present some draw- backs, like, for example, they work only for specific CPU architectures, or they require code instrumentation, or they have a different target (i.e., design errors instead of dependability analysis). To address these disadvantages, this paper presents an efficient fault injection approach based on QEMU, one of the most efficient and popular instruction-accurate emulator for several microprocessor architectures. As main goal, the proposed approach represents a non intrusive technique for simulating hardware faults affecting CPU behaviours. Perma- nent and transient/intermittent hardware fault models have been abstracted without losing quality for software dependability analysis. The approach mini- mizes the impact of the fault injection procedure in the emulator performance by preserving the original dynamic binary translation mechanism of QEMU. Experimental results for both x86 and ARM processors proving the efficiency and effectiveness of the proposed approach are presented

Interaction-resistant metals in multicomponent Fermi systems

We analyze two different fermionic systems that defy Mott localization showing a metallic ground state at integer filling and very large Coulomb repulsion. The first is a multiorbital Hubbard model with a Hund's coupling, where this physics has been widely studied and the new metallic state is called a Hund's metal, and the second is a SU(3) Hubbard model with a patterned single-particle potential designed to display a similar interaction-resistant metal in a set-up which can be implemented with SU($N$) ultracold atoms. With simple analytical arguments and exact numerical diagonalization of the Hamiltonians for a minimal three-site system, we demonstrate that the interaction-resistant metal emerges in both cases as a compromise between two different insulating solutions which are stabilized by different terms of the models. This provides a strong evidence that the Hund's metal is a specific realization of a more general phenomenon which can be realized in various strongly correlated systems.Comment: 11 pages, 11 figure

Preliminary study of the effects of ultrasound on red wine polyphenols

The article evaluates the effect of high-power ultrasound (20 kHz) on the phenolic structure of red wines, to study the possible applications of this innovative technique in wine aging. Different treatment conditions, with times of 1, 3 and 5 minutes and amplitudes of 51, 102 and 153 \u3bcm, were applied. In the experimental conditions the main parameters related to the evolution of red wine phenolic compounds show interesting variations; in particular, we found significant differences on tannins evaluated with some indices of tannins reactivity. On the other hand, free anthocyanins do not undergo changes due to ultrasound application. The preliminary results, which definitely need a depth, nonetheless allow us to hypothesize the application of ultrasound technology to accelerate the aging of red wines, which normally requires (needs) long times in the cellar condition

Fogão solar: ferramenta viável para cozimento de alimentos a partir de materiais de baixo custo

Trabalho apresentado no II Congresso Nacional do PROJETO RONDON, realizado em Florianópolis, SC, no período de 23 a 25 de setembro de 2015 - Universidade Federal de Santa Catarina.Na busca do desenvolvimento de projetos voltados à utilização de energia limpa e renovável, a energia solar vem ganhando destaque nos últimos anos. Esta configura-se como uma fonte de energia abundante e inesgotável, uma vez que é proveniente de fenômenos naturais e possibilita a captação e conversão em outras formas de energia. Estudos relatam a importância e viabilidade da utilização de muitos equipamentos, dentre estes, o fogão solar para cocção de vários alimentos. Deste modo, o presente estudo objetivou apresentar uma ferramenta viável e barata para fins de cozimento de alimentos e fervura (desinfecção) da água, a construção de um fogão solar tipo caixa, contribuindo com as futuras operações do Projeto Rondon, as quais têm lugar em regiões com forte incidência de luz solar, norte e nordeste do Brasil. Durante o evento I Jornada de Pesquisa, Extensão e Cultura- I Mostra de Projetos, realizado nos dias 4 a 8 de maio de 2015 na Faculdade de Tecnologia de Jundiaí (FATEC- JD), pode-se compreender o princípio de funcionamento de um fogão solar construído pelos alunos do Curso de Tecnologia em Gestão Ambiental (GAM), sendo possível identificar sua eficiência e bom desempenho ao realizar o cozimento de alimentos. A partir da Mostra de Projetos pensou-se na viabilidade do seu uso em comunidades carentes, principalmente, as que utilizam fogão a lenha, e em regiões com grande potencial solar, caso do Nordeste, podendo ser substituído, parcialmente, para o cozimento de determinados alimentos como arroz, macarrão, além da fervura da água

Nitrogen fluxes in forests from atmospheric deposition to soil: use of water flux monitoring and stable isotopes to close gaps in nitrogen transfers

Temperate forest ecosystems are significant sinks for atmospheric nitrogen (N) deposition (Ndep) yielding benefits such as protection of waterbodies from eutrophication and enhanced sequestration of atmospheric CO2. Many uncertainties remain about the fate of Ndep due to the different input fluxes and their spatial and temporal variation, the transformation between different N forms, the complexity of interactions between N and different forest ecosystem components, and the different methods used to quantify N stores and fluxes. Previously, many studies on the interaction between Ndep and forests have focused on Ndep at the soil level, assuming that the interaction between Ndep and the tree canopy is negligible. However, in the last 20 years an increasing number of studies showed how canopy uptake, calculated as the difference between the Ndep input and the fluxes below the canopy (throughfall and stemflow), accounted for a significant fraction of the total input. This could lead to an underestimation of the effects of Ndep on forest carbon sequestration. Moreover, transformations of N passing through the canopy might occur which can change the N dynamics and N availability in soil. Previous studies have shown evidence of biological nitrification and Ndep processing and retention at the canopy level. However, this was reported only at sites where Ndep levels were high or where low background levels were experimentally raised (up to 18 kg N ha-1 y-1). The aim of this research was to resolve in a low Ndep area, some uncertainties related to Ndep processing by forest canopies. The case study area was Griffin Forest (Perthshire, Scotland), a typical Sitka spruce plantation of the UK uplands, characterised by a generally low Ndep (5-9 kg ha-1 year-1 ). Field monitoring was conducted for 5 years of N fluxes in water onto and below the canopy, litter transfer from the canopy to the soil, and nitrous oxide (N2O) fluxes from forest soils. Comparison of rainfall (RF, or bulk precipitation) and cloudwater (CW) with throughfall (TF) and stemflow (SF) measured below the canopy suggests strong transformation and uptake of Ndep in the forest canopy. The annual mean canopy uptake (CU) of N (calculated as a balance of RF + CW – TF – SF) at Griffin Forest was 70%, and varied between 60% in 2014 and almost 80% in 2012. The data showed a significant long term decreasing trend in bulk deposition of NO3 - with peaks during the growing season and a significant strong positive correlation between bulk deposition and CU for NO3- N, NH4-N and total N. These results and a seasonal difference in results were confirmed through a labelled simulated Ndep experiment, where the top of the canopy of three selected trees was sprayed with a 15NH4 15NO3 (98%) - NH4NO3 solution on two occasions, one during the growing season and one in winter. Background RF and TF and SF below the trees were collected and analysed for 15NH4 and 15NO3. The N CU in summer (N% = 78±4.5; 15N% = 85.7±2.9) is much higher than the amount recovered in winter (N% = 51.3±11.9; 15N% = 43.7±14.2) suggesting at least a partial retention by the plant, together with possible transformations from inorganic to organic N and N gaseous losses. To assess actual plant retention more effectively direct application of a 15N solution to target branches in situ showed that ~14% of the applied N was recovered in needles and twigs after a period of 24 hours. The short time scale in which this recovery occurred and the particularly dry conditions during the experiment could lead to an underestimation of the actual potential N retention by the canopy as foliar uptake depends on leaf wetness, as literature suggests. The fate of organic N transfer to forest soils through litter was addressed through 15N-labelled litter plots sampled 2 and 4 years after the litter replacement. Results show that the different soil features typical of a forest plantation (ridge, undisturbed soil, and furrow) had different δ15N and estimated 15N recovery over time. The estimated maximum recovery was ≃52% in 2017 of which ~16% was found in roots. N2O-N losses from soil measured on a 3-year period showed a significant increase in time and they were positively correlate to reduced N bulk deposition. Their order of magnitude was similar to N losses through streamwater and represented a small portion of the atmospheric inputs. This research has shown that the effects of forest canopies on N deposition occurs at two levels. Firstly, at the canopy level there is consistent uptake of the N input, with only 30% or less directly reaching the soil as inorganic N. A second indirect effect is that the uptaken N, either directly by the plant or through bacterial/fungi sequestration at the phyllosphere level, is likely to be transferred to the soil as organic N via litter and here rapidly used by the plants. The water and gas flux monitoring showed that no major leaching occurs, indicating that the forest acts as a N sink. The research results confirm the highest figures in the literature of nitrogen canopy uptake. At the relatively low deposition rates present in the UK uplands, Ndep represents an important extra source of N to the forest N cycle. Lower N fluxes measured under the canopy, excluding the canopy effect and those taken under high 15N-N tracer additions, could underestimate the extra carbon sequestration induced by the Ndep. The research results and findings are relevant to understanding and modelling N cycling and its impacts on forest growth and carbon storage in similar forest systems in the UK uplands and at a broader scale under similar Ndep conditions

Tourist and Viral Mobilities Intertwined: Clustering COVID-19-Driven Travel Behaviour of Rural Tourists in South Tyrol, Italy

Travel patterns have dramatically changed during the COVID-19 pandemic. Tourism has been both a vector and a victim of the disease. This paper explores the pandemic’s impact on rural tourism, using the theoretical framework of the “mobilities turn” to investigate issues of corporeal and communicative travel found between the first and second waves of the COVID-19 pandemic. A sample of 874 guests visiting the Italian region of South Tyrol, where rural tourism is the norm, identified different patterns of physical travel and approaches to collecting on-site information on COVID-19. Results from a principal component analysis (PCA) and a cluster analysis highlighted at least two different approaches from visitors to the region: the first is more cautious, mostly practiced by domestic tourists, with limited mobility on-site, coupled with a need for information; the second is instead a more adventurous approach, with higher on-site mobility, more use of sustainable forms of transport and less interest in data evidence on COVID-19. Implications for rural tourism and its future are discussed. The hypothesis of an inverse relationship between corporeal and communicative travel needs further exploration in future research

Termodinamica di bosoni confinati e interagenti

The Bose-Einstein condensation (BEC) is a quantum phenomenon which was theorized in 1920s, but it was realized for the first time in the JILA Laboratory (University of Colorado, Boulder) by Eric Cornell and Carl Wieman only in 1995. Since 1995, lots of experiments on BEC have been realized using different gases and various conditions. One can give a correct interpretation of the results of these works only by considering the role of interaction between particles on relevant physical quantities, such as critical temperature and condensed fraction. The purpose of our work is deducing the main thermodynamic properties of trapped and interacting Bose gases using the tools of "traditional" Quantum Mechanics, avoiding the introduction of "second quantization" (which often recurs in litterature). The first chapter shows a derivation of the famous Gross-Pitaevskii equation, starting from the many-bodies Dirac action and applying the principle of least action. Moreover, two approximate solutions of this equation are discussed as well: the gaussian variational ansatz for weakly interacting particles, and the Thomas-Fermi approximation, for strongly interacting particles. In chapter 2 we derive the Bogoliubov dispersion relation for excited states (or quasiparticle energy spectrum) with the tools of Hamiltonian Mechanics and semiclassical approximation. Furthermore, we discuss some approximations for this formula (especially the Hartree-Fock spectrum for weakly interacting bosons) and we use the Bose-Einstein distribution to find the thermal cloud density. In chapter 3 we use the previous results to calculate explicit expressions for critical temperature and condensed fraction (where possible) in four particular cases: ideal free and trapped Bose gas, interacting free and trapped Bose gas. We also discuss the main results obtained by Giorgini, Pitaevskii and Stringari, who managed to explain accurately Cornell and Wieman's experimental plots. Finally we conclude that traditional Quantum Mechanics is quite efficient to derive the main equations of BEC and that introducing second quantization is not essential. Nevertheless, some issues remain unresolved in this context: for example the phenomenon of quantum depletion and the generalisation of the Gross-Pitaevskii equation at non-zero temperature.ope

ExaRanker: Explanation-Augmented Neural Ranker

Recent work has shown that inducing a large language model (LLM) to generate explanations prior to outputting an answer is an effective strategy to improve performance on a wide range of reasoning tasks. In this work, we show that neural rankers also benefit from explanations. We use LLMs such as GPT-3.5 to augment retrieval datasets with explanations and train a sequence-to-sequence ranking model to output a relevance label and an explanation for a given query-document pair. Our model, dubbed ExaRanker, finetuned on a few thousand examples with synthetic explanations performs on par with models finetuned on 3x more examples without explanations. Furthermore, the ExaRanker model incurs no additional computational cost during ranking and allows explanations to be requested on demand