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In the last years, the EU and scientific community put a lot of effort in trying to increase the sustainability in renovated buildings by introducing novel concepts and technologies. This paper presents the outcomes of a retrofit case study carried out within the Heat4Cool H2020 project concerning space heating (SH) and domestic hot water (DHW) systems. The case study is a multi-family residential building located in Chorzow, Poland, where the SH and DHW are provided by natural gas boilers present in each apartment. The proposed approach is to combine the existing gas boilers with phase change material storages (PCM) and a direct current air source heat pump (DC-EHP) assisted by a photovoltaic system (PV) connected to the grid. TRNSYS was used for the dynamic simulations, and to support the introduction of the retrofit layout. New custom TRNSYS’ types were developed for each technology and tested against experimental data provided by industrial partners. Furthermore, a state-of-the-art rule-based controller was developed combining TRNSYS with a MATLAB’s script and tested against an interior point optimal control algorithm. In the best-case scenario the yearly primary energy savings are more than 30% accounting for the PV energy sold to the grid and around 11% considering only self-consumption, while the pay-back time is around 10 years considering EU28 economic conditions and 20% overall discount for the renovation project.

In this work, novel composite silicone-SAPO-34 foams have been prepared and experimentally characterized for application in desiccant open cycles. Water adsorption isotherms of several samples have been measured by a gravimetric dynamic vapour sorption analyser at 30°C and 70°C up to the relative humidity RH= 75%, representing typical process and regeneration air conditions in desiccant evaporative cooling cycles. Adsorbent foams manufactured with 20%, 40% and 60% weight fraction of SAPO-34 have been compared with the pure SAPO-34 powder. Results highlighted that the prepared foams adsorb a significant amount of water, according to the initial mass fraction of zeolite used in the compound. Moreover, the tested foams exhibited sufficiently fast water sorption rate for practical application in a desiccant open cycle system.

The COVID-19 pandemic is a global traumatic experience for citizens, especially during sensitive time windows of heightened plasticity such as pregnancy and neonatal life. Pandemic-related stress experienced by mothers during pregnancy may act as an early risk factor for infants' regulatory capacity development by altering maternal psychosocial well-being (e.g., increased anxiety, reduced social support) and caregiving environment (e.g., greater parenting stress, impaired mother–infant bonding). The aim of the present longitudinal study was to assess the consequences of pandemic-related prenatal stress on infants' regulatory capacity. A sample of 163 mother–infant dyads was enrolled at eight maternity units in northern Italy. They provided complete data about prenatal stress, perceived social support, postnatal anxiety symptoms, parenting stress, mother–infant bonding, and infants' regulatory capacity at 3 months of age. Women who experienced emotional stress and received partial social support during pregnancy reported higher anxious symptoms. Moreover, maternal postnatal anxiety was indirectly linked to the infants' regulatory capacity at 3 months, mediated by parenting stress and mother–infant bonding. Dedicated preventive interventions should be delivered to mothers and should be focused on protecting the mother–infant dyad from the detrimental effects of pandemic-related stress during the COVID-19 healthcare emergency. [ABSTRACT FROM AUTHOR]

We propose an algorithm for accurate, systematic, and scalable computation of interatomic forces within the auxiliary-field quantum Monte Carlo (AFQMC) method. The algorithm relies on the Hellmann-Feynman theorem and incorporates Pulay corrections in the presence of atomic orbital basis sets. We benchmark the method for small molecules by comparing the computed forces with the derivatives of the AFQMC potential energy surface and by direct comparison with other quantum chemistry methods. We then perform geometry optimizations using the steepest descent algorithm in larger molecules. With realistic basis sets, we obtain equilibrium geometries in agreement, within statistical error bars, with experimental values. The increase in computational cost for computing forces in this approach is only a small prefactor over that of calculating the total energy. This paves the way for a general and efficient approach for geometry optimization and molecular dynamics within AFQMC. [ABSTRACT FROM AUTHOR]