Computation of H→ggH\to gg in FDH and DRED: renormalization, operator mixing, and explicit two-loop results

The $H\to gg$ amplitude relevant for Higgs production via gluon fusion is computed in the four-dimensional helicity scheme (FDH) and in dimensional reduction (DRED) at the two-loop level. The required renormalization is developed and described in detail, including the treatment of evanescent $\epsilon$-scalar contributions. In FDH and DRED there are additional dimension-5 operators generating the $H g g$ vertices, where $g$ can either be a gluon or an $\epsilon$-scalar. An appropriate operator basis is given and the operator mixing through renormalization is described. The results of the present paper provide building blocks for further computations, and they allow to complete the study of the infrared divergence structure of two-loop amplitudes in FDH and DRED

SCET approach to regularization-scheme dependence of QCD amplitudes

We investigate the regularization-scheme dependence of scattering amplitudes in massless QCD and find that the four-dimensional helicity scheme (FDH) and dimensional reduction (DRED) are consistent at least up to NNLO in the perturbative expansion if renormalization is done appropriately. Scheme dependence is shown to be deeply linked to the structure of UV and IR singularities. We use jet and soft functions defined in soft-collinear effective theory (SCET) to efficiently extract the relevant anomalous dimensions in the different schemes. This result allows us to construct transition rules for scattering amplitudes between different schemes (CDR, HV, FDH, DRED) up to NNLO in massless QCD. We also show by explicit calculation that the hard, soft and jet functions in SCET are regularization-scheme independent.Comment: 46 pages, 6 figure

Healthcare digitalization and pay-for-performance incentives in smart hospital project financing

This study aims to explore the impact of healthcare digitalization on smart hospital project financing (PF) fostered by pay-for-performance (P4P) incentives. Digital platforms are a technology-enabled business model that facilitates exchanges between interacting agents. They represent a bridging link among disconnected nodes, improving the scalable value of networks. Application to healthcare public-private partnerships (PPPs) is significant due to the consistency of digital platforms with health issues and the complexity of the stakeholder’s interaction. In infrastructural PPPs, public and private players cooperate, usually following PF patterns. This relationship is complemented by digitized supply chains and is increasingly patient-centric. This paper reviews the literature, analyzes some supply chain bottlenecks, addresses solutions concerning the networking effects of platforms to improve PPP interactions, and investigates the cost-benefit analysis of digital health with an empirical case. Whereas diagnostic or infrastructural technology is an expensive investment with long-term payback, leapfrogging digital applications reduce contingent costs. “Digital” savings can be shared by key stakeholders with P4P schemes, incentivizing value co-creation patterns. Efficient sharing may apply network theory to a comprehensive PPP ecosystem where stakeholding nodes are digitally connected. This innovative approach improves stakeholder relationships, which are re-engineered around digital platforms that enhance patient-centered satisfaction and sustainability. Digital technologies are useful even for infectious disease surveillance, like that of the coronavirus pandemic, for supporting massive healthcare intervention, decongesting hospitals, and providing timely big data

Agronomic approaches for characterization, remediation, and monitoring of contaminated sites

With a view to conserving or improving soil ecosystem services, environment-friendly techniques, such as bio- and phytoremediation, can effectively be used for the characterization, risk assessment, and remediation of contaminated agricultural sites. Polyannual vegetation (meadows, poplar, and cane stands) is widely considered the most efficient tool for remediation (extraction of bioavailable fraction of contaminants), for undertaking safety measures (reducing the mobility of contaminants towards other environmental compartments), and for restoring the ecosystem services of contaminated agricultural sites (biomass production, groundwater protection, C storage, landscape quality improvement, and cultural and educational services). The roles of agronomic approaches will be reviewed by focusing on the various steps in the whole remediation process: (i) detailed environmental characterization; (ii) phytoremediation for reducing risks for the environment and human health; (iii) agronomic management for improving efficiency of phytoremediation; and (iv) biomass recycling in the win-win perspective of the circular economy

Biofuel production with castor bean: A win-win strategy for marginal land

The urgency to reduce resource depletion and waste production is expected to lead to an economy based on renewable resources. Biofuels, for instance, are a great green alternative to fossil fuel, but they are currently derived from edible vegetable oils such as soybean, palm, and sunflower. Concerns have been raised about the social-economic implication and ecological impacts of biodiesel production. Cultivating new lands as biodiesel feedstock rather than food supply, with the consequent increase in food prices, leads to so-called indirect land-use change (ILUC). Establishing bioenergy crops with phytoremediation ability on contaminated soils offers multiple benefits such as improving soil properties and ecosystem services, decreasing soil erosion, and diminishing the dispersion of potentially toxic elements (PTEs) into the environment. Castor bean is an unpalatable, high-biomass plant, and it has been widely demonstrated to possess phytoremediation capability for several PTEs. Castor bean can grow on marginal lands not suitable for food crops, has multiple uses as a raw material, and is already used in biodiesel production. These characteristics make it perfect for sustainable biodiesel production. Linking biofuel production with environmental remediation can be considered a win-win strategy

Can public-private partnerships foster investment sustainability in smart hospitals?

This article addresses the relationship between Public-Private Partnerships (PPP) and the sustainability of public spending in smart hospitals. Smart (technological) hospitals represent long-termed investments where public and private players interact with banking institutions and eventually patients, to satisfy a core welfare need. Characteristics of smart hospitals are critically examined, together with private actors' involvement and flexible forms of remuneration. Technology-driven smart hospitals are so complicated that they may require sophisticated PPP. Public players lack innovative skills, whereas private actors seek additional compensation for their non-routine efforts and higher risk. PPP represents a feasible framework, especially if linked to Project Financing (PF) investment patterns. Whereas the social impact of healthcare investments seems evident, their financial coverage raises growing concern in a capital rationing context where shrinking public resources must cope with the growing needs of chronic elder patients. Results-Based Financing (RBF) is a pay-by-result methodology that softens traditional PPP criticalities as availability payment sustainability or risk transfer compensation. Waste of public money can consequently be reduced, and private bankability improved. In this study, we examine why and how advanced Information Technology (IT) solutions implemented in "Smart Hospitals" should produce a positive social impact by increasing at the same time health sustainability and quality of care. Patient-centered smart hospitals realized through PPP schemes, reshape traditional healthcare supply chains with savings and efficiency gains that improve timeliness and execution of care

Comment on "Local accumulation times for source, diffusion, and degradation models in two and three dimensions" [J. Chem. Phys. 138, 104121 (2013)]

In a recent paper, Gordon, Muratov, and Shvartsman studied a partial differential equation (PDE) model describing radially symmetric diffusion and degradation in two and three dimensions. They paid particular attention to the local accumulation time (LAT), also known in the literature as the mean action time, which is a spatially dependent timescale that can be used to provide an estimate of the time required for the transient solution to effectively reach steady state. They presented exact results for three-dimensional applications and gave approximate results for the two-dimensional analogue. Here we make two generalizations of Gordon, Muratov, and Shvartsman’s work: (i) we present an exact expression for the LAT in any dimension and (ii) we present an exact expression for the variance of the distribution. The variance provides useful information regarding the spread about the mean that is not captured by the LAT. We conclude by describing further extensions of the model that were not considered by Gordon,Muratov, and Shvartsman. We have found that exact expressions for the LAT can also be derived for these important extensions..

Mixing and reaction efficiency in closed domains

We present a numerical study of mixing and reaction efficiency in closed domains. In particular we focus our attention on laminar flows. In the case of inert transport the mixing properties of the flows strongly depend on the details of the Lagrangian transport. We also study the reaction efficiency. Starting with a little spot of product we compute the time needed to complete the reaction in the container. We found that the reaction efficiency is not strictly related to the mixing properties of the flow. In particular, reaction acts as a "dynamical regulator".Comment: 11 pages, 10 figure

A Multi-Source Harvesting System Applied to Sensor-Based Smart Garments for Monitoring Workers’ Bio-Physical Parameters in Harsh Environments

This paper describes the development and characterization of a smart garment for monitoring the environmental and biophysical parameters of the user wearing it; the wearable application is focused on the control to workers’ conditions in dangerous workplaces in order to prevent or reduce the consequences of accidents. The smart jacket includes flexible solar panels, thermoelectric generators and flexible piezoelectric harvesters to scavenge energy from the human body, thus ensuring the energy autonomy of the employed sensors and electronic boards. The hardware and firmware optimization allowed the correct interfacing of the heart rate and SpO2 sensor, accelerometers, temperature and electrochemical gas sensors with a modified Arduino Pro mini board. The latter stores and processes the sensor data and, in the event of abnormal parameters, sends an alarm to a cloud database, allowing company managers to check them via a web app. The characterization of the harvesting subsection has shown that ≈ 265 mW maximum power can be obtained in a real scenario, whereas the power consumption due to the acquisition, processing and BLE data transmission functions determined that a 10 mAh/day charge is required to ensure the device’s proper operation. By charging a 380 mAh Lipo battery in a few hours by means of the harvesting system, an energy autonomy of 23 days was obtained, in the absence of any further energy contribution