Experimental device-independent certified randomness generation with an instrumental causal structure

The intrinsic random nature of quantum physics offers novel tools for the generation of random numbers, a central challenge for a plethora of fields. Bell non-local correlations obtained by measurements on entangled states allow for the generation of bit strings whose randomness is guaranteed in a device-independent manner, i.e. without assumptions on the measurement and state-generation devices. Here, we generate this strong form of certified randomness on a new platform: the so-called instrumental scenario, which is central to the field of causal inference. First, we theoretically show that certified random bits, private against general quantum adversaries, can be extracted exploiting device-independent quantum instrumental-inequality violations. To that end, we adapt techniques previously developed for the Bell scenario. Then, we experimentally implement the corresponding randomness-generation protocol using entangled photons and active feed-forward of information. Moreover, we show that, for low levels of noise, our protocol offers an advantage over the simplest Bell-nonlocality protocol based on the Clauser-Horn-Shimony-Holt inequality.Comment: Modified Supplementary Information: removed description of extractor algorithm introduced by arXiv:1212.0520. Implemented security of the protocol against general adversarial attack

Multi-Source Diffusion Models for Simultaneous Music Generation and Separation

In this work, we define a diffusion-based generative model capable of both music synthesis and source separation by learning the score of the joint probability density of sources sharing a context. Alongside the classic total inference tasks (i.e., generating a mixture, separating the sources), we also introduce and experiment on the partial generation task of source imputation, where we generate a subset of the sources given the others (e.g., play a piano track that goes well with the drums). Additionally, we introduce a novel inference method for the separation task based on Dirac likelihood functions. We train our model on Slakh2100, a standard dataset for musical source separation, provide qualitative results in the generation settings, and showcase competitive quantitative results in the source separation setting. Our method is the first example of a single model that can handle both generation and separation tasks, thus representing a step toward general audio models.Comment: Demo page: https://gladia-research-group.github.io/multi-source-diffusion-models

Latent Autoregressive Source Separation

Autoregressive models have achieved impressive results over a wide range of domains in terms of generation quality and downstream task performance. In the continuous domain, a key factor behind this success is the usage of quantized latent spaces (e.g., obtained via VQ-VAE autoencoders), which allow for dimensionality reduction and faster inference times. However, using existing pre-trained models to perform new non-trivial tasks is difficult since it requires additional fine-tuning or extensive training to elicit prompting. This paper introduces LASS as a way to perform vector-quantized Latent Autoregressive Source Separation (i.e., de-mixing an input signal into its constituent sources) without requiring additional gradient-based optimization or modifications of existing models. Our separation method relies on the Bayesian formulation in which the autoregressive models are the priors, and a discrete (non-parametric) likelihood function is constructed by performing frequency counts over latent sums of addend tokens. We test our method on images and audio with several sampling strategies (e.g., ancestral, beam search) showing competitive results with existing approaches in terms of separation quality while offering at the same time significant speedups in terms of inference time and scalability to higher dimensional data.Comment: Accepted to AAAI 202

Accelerating Transformer Inference for Translation via Parallel Decoding

Autoregressive decoding limits the efficiency of transformers for Machine Translation (MT). The community proposed specific network architectures and learning-based methods to solve this issue, which are expensive and require changes to the MT model, trading inference speed at the cost of the translation quality. In this paper, we propose to address the problem from the point of view of decoding algorithms, as a less explored but rather compelling direction. We propose to reframe the standard greedy autoregressive decoding of MT with a parallel formulation leveraging Jacobi and Gauss-Seidel fixed-point iteration methods for fast inference. This formulation allows to speed up existing models without training or modifications while retaining translation quality. We present three parallel decoding algorithms and test them on different languages and models showing how the parallelization introduces a speedup up to 38% w.r.t. the standard autoregressive decoding and nearly 2x when scaling the method on parallel resources. Finally, we introduce a decoding dependency graph visualizer (DDGviz) that let us see how the model has learned the conditional dependence between tokens and inspect the decoding procedure.Comment: Accepted at ACL 2023 main conferenc

Bioaccumulation of Trace Elements in the Muscle of the Blackmouth Catshark Galeus melastomus from Mediterranean Waters

Environmental pollution, particularly in the marine environment, has become a significant concern due to the increasing presence of pollutants and their adverse effects on ecosystems and human health. This study focuses on the bioaccumulation of trace elements in the muscle tissue of the blackmouth catshark (Galeus melastomus) from different areas in the Mediterranean Sea. Trace elements are of interest due to their persistence, toxicity, and potential for bioaccumulation. This research aims to assess the distribution and accumulation of trace elements in the muscle tissue of G. melastomus and investigate their potential impact on the deep-sea environment of the Mediterranean. The focused areas include the Ligurian Sea, the northern and central Tyrrhenian Sea, the southern Tyrrhenian Sea, the Ionian Sea, the Pantelleria Waters, and the Gela Waters. Samples were collected following established protocols, and trace element analysis was conducted using inductively coupled plasma mass spectrometry. The study provides data on the concentrations of 17 trace elements, namely aluminum, arsenic, cadmium, cobalt, copper, manganese, molybdenum, nickel, zinc, selenium, strontium, lead, chromium, iron, barium, bismuth, and uranium. The findings contribute to a better understanding of trace element bioaccumulation patterns in elasmobranch species, specifically G. melastomus, and highlight the potential risks associated with chemical contamination in the Mediterranean Sea. This research emphasizes the importance of studying the impacts of pollutants on marine organisms, particularly those occupying key ecological roles, like sharks, to support effective conservation and management strategies

A cross-sectional study evaluating hospitalization rates for chronic limb-threatening ischemia during the COVID-19 outbreak in Campania, Italy

The expansion of coronavirus disease 2019 (COVID-19) prompted measures of disease containment by the Italian government with a national lockdown on March 9, 2020. The purpose of this study is to evaluate the rate of hospitalization and mode of in-hospital treatment of patients with chronic limb-threatening ischemia (CLTI) before and during lockdown in the Campania region of Italy. The study population includes all patients with CLTI hospitalized in Campania over a 10-week period: 5 weeks before and 5 weeks during lockdown (n = 453). Patients were treated medically and/or underwent urgent revascularization and/or major amputation of the lower extremities. Mean age was 69.2 +/- 10.6 years and 27.6% of the patients were women. During hospitalization, 21.9% of patients were treated medically, 78.1% underwent revascularization, and 17.4% required amputations. In the weeks during the lockdown, a reduced rate of hospitalization for CLTI was observed compared with the weeks before lockdown (25 vs 74/100,000 inhabitants/year; incidence rate ratio: 0.34, 95% CI 0.32-0.37). This effect persisted to the end of the study period. An increased amputation rate in the weeks during lockdown was observed (29.3% vs 13.4%; p < 0.001). This study reports a reduced rate of CLTI-related hospitalization and an increased in-hospital amputation rate during lockdown in Campania. Ensuring appropriate treatment for patients with CLTI should be prioritized, even during disease containment measures due to the COVID-19 pandemic or other similar conditions

Three finned press-fit cup: Does its initial fixation strength provide an adequate stability? Clinical midterm results of 685 implants

Introduction: One of the major causes of loosening of cementless acetabular cup implants is insufficient initial stability. A technical proposal to decrease the risk of suboptimal first stability is a circumferential finned design of the cup. This design aims to improve periacetabular bone contact and prevent rotational micromotion of the cup when optimal press-fit cannot be obtained. Materials and Methods: We retrospectively reviewed a group of 712 consecutive patients who underwent total hip arthroplasty from June 2006 to June 2014. In all patients, a titanium cup, characterized by three anti-rotational circumferential fins at the superior pole, was implanted. Results: Five hundred and ninety-two patients, for a total of 685 hips, were evaluated at a mean follow-up of 58 months (range 12-96 months). At 1-year follow-up, the average score increased to 82.90 (range 100-70) and at the final follow-up (58 months, range 12-96 months), it was 80.12 (range 100-66). In 22 cases (3%), screws to obtain a secure primary stability of the cup were used. Nineteen complications (2.6%) needing revision surgery were observed. Survivorship at 10 years was 98.7% (95% confidence interval [CI], 98.7-99.7%) with revision for aseptic cup loosening as an endpoint and 96.7% (95% CI, 98.3-95.1%) with revision for all causes of revision as the second endpoint. Discussion: In our group of patients, we did not observe the cases of very early cup loosening. The only two-cup revision, do to loosening of osteolysis, was observed 26 and 32 months before surgery. Conclusion: Our very low rate of additional screws represents an indirect sign of finned cup first stability. Three-finned cup design clinically confirmed to improve initial cup stability

Natural <i>versus</i> anthropogenic influences on the chemical composition of bulk precipitation in the southern Apennines, Italy: a case study of the town of Potenza

This paper presents new data on the chemical composition of precipitation in a selected area of the southern Apennines of Italy; these data are used to assess natural and anthropogenic contributions to the precipitation. The town of Potenza was used as a representative urban site, and the major and minor element (Na+, K+, Ca2+, Mg2+, NH+4, Cl−, NO-3, SO2−4, and Li+, NO-2, F−, Br−, PO3−4) and trace element (Zn, Fe, Al, Sr, Mn, Ba, Cu, Cr, V, As, Pb, Ni, and Cd) concentrations of bulk precipitation from three different sampling sites within the study area were determined between June 2011 and May 2012. The majority of the collected rainwater has pH values higher than 5.6. The composition of this rainwater was dominated by Ca2+ the element with the highest total volume-weightedmean concentration (TVWA), followed by Cl−, SO2−4, Na+, NO−3, K+,Mg2+, and NH+4. The TVWA of the trace metals decreased in the order Zn N Fe N Al N Ba N Sr N Mn N Pb N Cu N As. Neutralising factor (NFXi) values indicate that Ca2+ is the dominant neutralising cation within this rainwater, with lower contribution from NH+4 and Mg2+. The precipitation analysed during this study has a negligible marine influence as determined using Cl− concentrations as a proxy for the abundance of sea salts. Precipitation Fi values (marine fraction of element i) indicate that Na+ is the element with the highest seawater component, and we found partial marine contributions for the SO2−4 and Mg2+ concentrations within this rainwater. Enrichment factors (EF) of selected elements were calculated to identify the sources of non-crustal elements: K+, Mg2+, Fe, and Ca2+ are the only elements dominantly sourced from the crust, whereas Mn and Ba have highly variable EF values (10–100) suggesting that a small proportion of these elements was derived from anthropogenic sources in addition to a more significant crustal contribution. Sr, Cu, Pb, Zn, and As are highly enriched with respect to average crustal compositions, confirming that the concentrations of these elements within precipitation are significantly controlled by human activities