Covid-19 Pandemic and the Fiscal Strategy of the International Monetary Fund: Towards New Directions in the Global Political Economy?

This article seeks to contribute to the analyses of the impact of the Covid-19 on the global political economy. It does so through a qualitative content analysis of the key policy documents published by the International Monetary Fund (IMF) since the outbreak of the pandemic crisis. The IMF has been, historically, one of the main designers of international macroeconomic governance. The paper focuses on fiscal policy, which retains a central place in the strategy of the IMF to deal with the pandemic and especially for the post-pandemic recovery phase. The analysis of the documents of the IMF contributes (i) to appreciate the interpretation of the nature of the pandemic crisis through the lenses of a prominent international financial institution, (ii) to explore the policy strategy outlined to deal with the pandemic emergency, (iii) to assess possible changes at the level of policy, and accordingly, future directions in global political economy. Evidence suggests that fiscal stimulus, public investment and planning will likely have a prominent position in the future directions of the IMF policy advice

Implementazione di un sistema per il self-management del diabete di tipo 1

Il diabete mellito è una malattia cronica che causa un'elevata concentrazione di glucosio nel sangue, superiore ai valori di riferimento, per lunghi periodi di tempo. La convivenza con questa patologia cronica può causare delle problematiche nella vita quotidiana. Al fine di ridurre le problematiche, oltre a seguire le prescrizioni mediche, degli accorgimenti sull'alimentazione e sull'attività fisica possono risultare fondamentali. Le persone affette da diabete, che decidono di intraprendere un percorso in cui adottano uno stile di vita più salutare, necessitano di continue informazioni sul proprio stato di salute; al fine di prendere la migliore decisione possibile. L'obiettivo di questa tesi, pertanto, è quello di realizzare un sistema in grado di fornire gli strumenti necessari per il self-Management del diabete mellito di tipo 1, adottando la visione dell'Internet of Things e del mobile Health. Nel dettaglio, si vuole realizzare un sistema che consenta all'assistito di simulare il proprio andamento glicemico attraverso il proprio smartphone; con lo scopo di ricevere dei consigli sull'alimentazione e sull'attività fisica da seguire

Are GAN generated images easy to detect? A critical analysis of the state-of-the-art

The advent of deep learning has brought a significant improvement in the quality of generated media. However, with the increased level of photorealism, synthetic media are becoming hardly distinguishable from real ones, raising serious concerns about the spread of fake or manipulated information over the Internet. In this context, it is important to develop automated tools to reliably and timely detect synthetic media. In this work, we analyze the state-of-the-art methods for the detection of synthetic images, highlighting the key ingredients of the most successful approaches, and comparing their performance over existing generative architectures. We will devote special attention to realistic and challenging scenarios, like media uploaded on social networks or generated by new and unseen architectures, analyzing the impact of suitable augmentation and training strategies on the detectors' generalization ability.Comment: 7 pages, 5 figures, conferenc

Enhancing Random Forest Classification with NLP in DAMEH: A system for DAta Management in EHealth Domain

The use of pervasive IoT devices in Smart Cities, have increased the Volume of data produced in many and many field. Interesting and very useful applications grow up in number in E-health domain, where smart devices are used in order to manage huge amount of data, in highly distributed environments, in order to provide smart services able to collect data to fill medical records of patients. The problem here is to gather data, to produce records and to analyze medical records depending on their contents. Since data gathering involve very different devices (not only wearable medical sensors, but also environmental smart devices, like weather, pollution and other sensors) it is very difficult to classify data depending their contents, in order to enable better management of patients. Data from smart devices couple with medical records written in natural language: we describe here an architecture that is able to determine best features for classification, depending on existent medical records. The architecture is based on pre-filtering phase based on Natural Language Processing, that is able to enhance Machine learning classification based on Random Forests. We carried on experiments on about 5000 medical records from real (anonymized) case studies from various health-care organizations in Italy. We show accuracy of the presented approach in terms of Accuracy-Rejection curves

An HPLC-automated Derivatization for Glutathione and Related Thiols Analysis in Brassica rapa L

The high content of glucosinolates and glutathione makes the Brassicaceae an important healthy food. Thiols and especially glutathione and γ-Glu-Cys-Gly tripeptide are involved in many fundamental cellular functions such as oxidative stress protection. Although several methods for sulphur compounds analysis in biological samples are actually used, the determination of glutathione and other sulphur derivatives in plant tissues is rather problematic due to their extreme susceptibility to oxidation, which can lead to their overestimation. The aim of this work was the improvement and validation of an automated method for determination of reduced and oxidised glutathione, cysteine and γ-glutamylcysteine in plant tissues. The method consists of a fully automated pre-column derivatization of thiols based on monobromobimane reagent, a high-performance liquid chromatography derivatives separation, and a fluorimetric detection and quantification. The method was successfully applied for determination of the oxidized and reduced forms of Cys, γ-GC and GSH content in leaves, petioles, inflorescences and roots of Brassica rapa L. subsp. Sylvestris. At harvest, in freshly cut plants, the average contents of GSH/2GSSG were 840/45, 345/70 and 150/70 nmol g−1 FW for the florets, leaf blades and stems, respectively; those of Cys/2Cys were 80/12, 29/12 and 24/6 nmol g-1 FW; while those of γ-GC/γ-GCCG-γ were 8.0/4.0, and 6.0/3.0, 3.0/2.0 nmol g−1 FW, respectively. Such amounts were lower in low-sulphur-grown plants at harvest. The very low coefficient of variation between repeated tests (maximum 1.6%), the high recovery of internal standard (>96%) and the linear correlation coefficient of the calibration (R2 > 0.99) support the efficiency of this method that allowed analysing about 50 samples/die in a totally automated manner with no operator intervention. Our results show that the reported method integrations can significantly improve thiols detection via HPL

Modified versus standard intention-to-treat reporting: Are there differences in methodological quality, sponsorship, and findings in randomized trials? A cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Randomized controlled trials (RCTs) that use the modified intention-to-treat (mITT) approach are increasingly being published. Such trials have a preponderance of post-randomization exclusions, industry sponsorship, and favourable findings, and little is known whether in terms of these items mITT trials are different with respect to trials that report a standard intention-to-treat.</p> <p>Methods</p> <p>To determine differences in the methodological quality, sponsorship, authors' conflicts of interest, and findings among trials with different "types" of intention-to-treat, we undertook a cross-sectional study of RCTs published in 2006 in three general medical journals (the Journal of the American Medical Association, the New England Journal of Medicine and the Lancet) and three specialty journals (Antimicrobial Agents and Chemotherapy, the American Heart Journal and the Journal of Clinical Oncology). Trials were categorized based on the "type" of intention-to-treat reporting as follows: ITT, trials reporting the use of standard ITT approach; mITT, trials reporting the use of a "modified intention-to-treat" approach; and "no ITT", trials not reporting the use of any intention-to-treat approach. Two pairs of reviewers independently extracted the data in duplicate. The strength of the associations between the "type" of intention-to-treat reporting and the quality of reporting (sample size calculation, flow-chart, lost to follow-up), the methodological quality of the trials (sequence generation, allocation concealment, and blinding), the funding source, and the findings was determined. Odds ratios (OR) were calculated with 95% confidence intervals (CI).</p> <p>Results</p> <p>Of the 367 RCTs included, 197 were classified as ITT, 56 as mITT, and 114 as "no ITT" trials. The quality of reporting and the methodological quality of the mITT trials were similar to those of the ITT trials; however, the mITT trials were more likely to report post-randomization exclusions (adjusted OR 3.43 [95%CI, 1.70 to 6.95]; <it>P </it>< 0.001). We found a strong association between trials classified as mITT and for-profit agency sponsorship (adjusted OR 7.41 [95%CI, 3.14 to 17.48]; <it>P </it>< .001) as well as the presence of authors' conflicts of interest (adjusted OR 5.14 [95%CI, 2.12 to 12.48]; <it>P </it>< .001). There was no association between mITT reporting and favourable results; in general, however, trials with for-profit agency sponsorship were significantly associated with favourable results (adjusted OR 2.30; [95%CI, 1.28 to 4.16]; <it>P </it>= 0.006).</p> <p>Conclusion</p> <p>We found that the mITT trials were significantly more likely to perform post-randomization exclusions and were strongly associated with industry funding and authors' conflicts of interest.</p

Calcium-sensing receptor and calcium kidney stones

Calcium nephrolithiasis may be considered as a complex disease having multiple pathogenetic mechanisms and characterized by various clinical manifestations. Both genetic and environmental factors may increase susceptibility to calcium stones; therefore, it is crucial to characterize the patient phenotype to distinguish homogeneous groups of stone formers. Family and twin studies have shown that the stone transmission pattern is not mendelian, but complex and polygenic. In these studies, heritability of calcium stones was calculated around 50

Pilot study on epigenetic response to a mind-body treatment

In the last years, epigenetics and functional genomics methods to evaluate the genomic effects and mechanisms of mind-body therapies have increasingly grown. DNA microarray technology has been used to show the involvement of the stress response pathways both in the case of disease and stress and as an effect of mind-body therapies. In the present research, the DNA samples obtained from 20 individuals who experienced a mind-body therapeutic protocol (MBT-T), were analysed from the bio-molecular point of view by means of an epigenetic marker (MSAP molecular tool), in order to estimate the different status of methylation. The subjects were compared at 3 different times: prior to, 1 hour after, and 24 hours after the treatment. The molecular data were processed through different biostatistics approaches: the Bayesian statistics approach, in order to estimate the clustering membership of the subjects (Structure), and the statistical estimation of the DNA methylation level (MSAP statistical tool). The structure analysis revealed that the clusters and their membership changed among the three time points moving from higher heterogeneous distribution to higher homogeneous clusters. Before the treatment, the subjects’ epigenetic profiles were heterogeneous; after the mind-body treatment we found that epigenetic profiles converged to homogeneous DNA methylation status. DNA epigenetic status of the subjects was affected by the MBT-T treatment