Health economic evaluation of Covid-19 vaccines: a systematic literature review

The outbreak of the COVID-19 pandemic provoked more than six million deaths worldwide between 2019 and 2022 andposed a heavy burden on the healthcare systems. The initial non-pharmaceutical interventions to mitigate the spread of the virus proved to be not sustainable in the long run due to excessive productivity losses. Governments, academic and the private sector invested to produce efficient and safe vaccines. Vaccines are evaluated primarily by their clinical outcomes. However, Health Economic Evaluations of COVID-19 vaccines are also an important tool for policy makers to determine the optimal vaccination strategy in their countries. The existing economic literature about COVID-19 vaccines includes cost-benefit and cost-effectiveness analysis, based on real world evidence (RWE) as well as modelling studies.The objective of this Systematic Literature Review isto report the main evidence from the economic evaluations of the vaccination programsagainst COVID-19that have been made as of summer 2022. Data on key economic outcomes were extracted from 16 scientific papers, selected from an initial list of 1842 studies on the PubMed database. The criteria for inclusion of the studies in this research considered specific restrictions for population, intervention, outcomes, and study design characteristics. The results were then reported following the Cochrane Handbook for Systematic Literature Review. The results indicate that Covid-19 vaccines and vaccination programs are cost-effective and have a positive impact on countries from a social and economic perspective

Data Flow ORB-SLAM for Real-time Performance on Embedded GPU Boards

The use of embedded boards on robots, including unmanned aerial and ground vehicles, is increasing thanks to the availability of GPU equipped low-cost embedded boards in the market. Porting algorithms originally designed for desktop CPUs on those boards is not straightforward due to hardware limitations. In this paper, we present how we modified and customized the open source SLAM algorithm ORB-SLAM2 to run in real-time on the NVIDIA Jetson TX2. We adopted a data flow paradigm to process the images, obtaining an efficient CPU/GPU load distribution that results in a processing speed of about 30 frames per second. Quantitative experimental results on four different sequences of the KITTI datasets demonstrate the effectiveness of the proposed approach. The source code of our data flow ORB-SLAM2 algorithm is publicly available on GitHub

Polar distortions in hydrogen bonded organic ferroelectrics

Although ferroelectric compounds containing hydrogen bonds were among the first to be discovered, organic ferroelectrics are relatively rare. The discovery of high polarization at room temperature in croconic acid [Nature \textbf{463}, 789 (2010)] has led to a renewed interest in organic ferroelectrics. We present an ab-initio study of two ferroelectric organic molecular crystals, 1-cyclobutene-1,2-dicarboxylic acid (CBDC) and 2-phenylmalondialdehyde (PhMDA). By using a distortion-mode analysis we shed light on the microscopic mechanisms contributing to the polarization, which we find to be as large as 14.3 and 7.0\,$\mu$C/cm$^{2}$ for CBDC and PhMDA respectively. These results suggest that it may be fruitful to search among known but poorly characterized organic compounds for organic ferroelectrics with enhanced polar properties suitable for device applications.Comment: Submitte

Performance of the first reverse electrodialysis pilot plant for power production from saline waters and concentrated brines

This work reports experimental data collected for the first time on a full-scale RED pilot plant operated with natural streams in a real environment. The plant - located in the South of Italy - represents the final accomplishment of the REAPower project (www.reapower.eu). A RED unit equipped with almost 50m2 of IEMs (125 cell pairs, 44x44cm2) was tested, using both artificial and natural feed solutions, these latter corresponding to brackish water (≈0.03M NaClequivalent) and saturated brine (4-5M NaClequivalent). A power output up to around 40W (i.e. 1.6W/m2 of cell pair) was reached using natural solutions, while an increase of 60% was observed when testing the system with artificial NaCl solutions, reaching up to ≈65W (2.7W/m2 of cell pair). The unit performance was monitored over a period of five months under, and no significant performance losses were observed due to scaling, fouling or ageing phenomena. Such results are of paramount importance to assess the potential of the technology, towards the successful development on the industrial scale. A scale-up of the pilot plant is planned through the installation of two additional RED modules, with an expected power output in the order of 1 kW

On the Asymptotic Dynamics of a Quantum System Composed by Heavy and Light Particles

We consider a non relativistic quantum system consisting of $K$ heavy and $N$ light particles in dimension three, where each heavy particle interacts with the light ones via a two-body potential $\alpha V$. No interaction is assumed among particles of the same kind. Choosing an initial state in a product form and assuming $\alpha$ sufficiently small we characterize the asymptotic dynamics of the system in the limit of small mass ratio, with an explicit control of the error. In the case K=1 the result is extended to arbitrary $\alpha$. The proof relies on a perturbative analysis and exploits a generalized version of the standard dispersive estimates for the Schr\"{o}dinger group. Exploiting the asymptotic formula, it is also outlined an application to the problem of the decoherence effect produced on a heavy particle by the interaction with the light ones.Comment: 38 page

On Quantum State Observability and Measurement

We consider the problem of determining the state of a quantum system given one or more readings of the expectation value of an observable. The system is assumed to be a finite dimensional quantum control system for which we can influence the dynamics by generating all the unitary evolutions in a Lie group. We investigate to what extent, by an appropriate sequence of evolutions and measurements, we can obtain information on the initial state of the system. We present a system theoretic viewpoint of this problem in that we study the {\it observability} of the system. In this context, we characterize the equivalence classes of indistinguishable states and propose algorithms for state identification

Diffusion-weighted MRI radiomics of spine bone tumors: feature stability and machine learning-based classification performance

Purpose To evaluate stability and machine learning-based classification performance of radiomic features of spine bone tumors using diffusion- and T2-weighted magnetic resonance imaging (MRI). Material and methods This retrospective study included 101 patients with histology-proven spine bone tumor (22 benign; 38 primary malignant; 41 metastatic). All tumor volumes were manually segmented on morphologic T2-weighted sequences. The same region of interest (ROI) was used to perform radiomic analysis on ADC map. A total of 1702 radiomic features was considered. Feature stability was assessed through small geometrical transformations of the ROIs mimicking multiple manual delineations. Intraclass correlation coefficient (ICC) quantified feature stability. Feature selection consisted of stability-based (ICC > 0.75) and significance-based selections (ranking features by decreasing Mann-Whitney p-value). Class balancing was performed to oversample the minority (i.e., benign) class. Selected features were used to train and test a support vector machine (SVM) to discriminate benign from malignant spine tumors using tenfold cross-validation. Results A total of 76.4% radiomic features were stable. The quality metrics for the SVM were evaluated as a function of the number of selected features. The radiomic model with the best performance and the lowest number of features for classifying tumor types included 8 features. The metrics were 78% sensitivity, 68% specificity, 76% accuracy and AUC 0.78. Conclusion SVM classifiers based on radiomic features extracted from T2- and diffusion-weighted imaging with ADC map are promising for classification of spine bone tumors. Radiomic features of spine bone tumors show good reproducibility rates

Gender may be related to the side of the motor syndrome and cognition in idiopathic Parkinson's disease.

Abstract Background and Sex and cognitive profile may be related to the laterality of motor symptoms in idiopathic Parkinson's disease. Introduction Parkinson's disease (PD) is well recognised as an inherently asymmetric disease with unilateral onset of motor symptoms. The laterality of motor symptoms may be linked to sex, clinical and demographic variables, and neuropsychological disorders. However, the available data are inconsistent. This study aimed to explore the potential association between the laterality of motor symptoms and clinical and demographic variables and deficits in specific cognitive domains. Material and methods We retrospectively recruited 97 participants with idiopathic PD without dementia; 60 presented motor symptoms on the left side and 37 on the right side. Both groups were comparable in terms of age, age at disease onset, disease duration, and severity of the neurological deficits according to the Unified Parkinson's Disease Rating Scale and the Hoehn and Yahr scale. Results Participants with left-side motor symptoms scored lower on the Schwab and England Activities of Daily Living scale. Our sample included more men than women (67% vs. 33%). Both sexes were not equally represented in the 2 groups: there were significantly more men than women in the group of patients with left-side motor symptoms (77% vs. 23%), whereas the percentages of men and women in the group of patients with right-side motor symptoms were similar (51% vs. 49%). Both groups performed similarly in all neuropsychological tasks, but women, independently of laterality, performed better than men in the naming task. Conclusion We found a clear prevalence of men in the group of patients with left-side motor symptoms; this group also scored lower on the Schwab and England Scale. Female sex was predictive of better performance in the naming task. Sex should always be considered in disorders that cause asymmetric involvement of the brain, such as PD

Superconducting Vortex‐Antivortex Pairs: Nucleation and Confinement in Magnetically Coupled Superconductor‐Ferromagnet Hybrids

Superconducting vortices are a well known class of vortices, each of them carrying a single magnetic flux quantum. In this chapter the authors present the results of low temperature Magnetic Force Microscopy experiments to investigate the nucleation and dynamics of superconducting vortices in magnetically coupled Superconductor/Ferromagnet (S/F) heterostructures made by Nb/Py. It is here shown that by controlling the thicknesses of both S and F layer, the formation of spontaneous vortex-antivortex pairs (V-AV) can be favored and their confinement and mobility can be tuned. The experimental results are compared with two theoretical models dealing with the spontaneous nucleation of V/AV pairs in the limits of S thickness respectively greater and smaller than the London penetration depth. It is shown that vortex nucleation and confinement is regulated by the intensity of the out-of-plane component of the magnetization with respect to a critical magnetization set by the thickness of both S and F layers. Additionally, external field cooling processes were used to probe in-field vortex nucleation and V-AV unbalancing, whereas the sweeping of an external magnetic field when below the superconducting critical temperature was used to force the vortex into motion, probing the vortex mobility/rigidity and the vortex avalanche events