Graphene nanoplatelets composite membranes for thermal comfort enhancement in performance textiles

The advent of 2D nanostructured materials as advanced fillers for polymer matrix composites has opened the doors to a plethora of new industrial applications requiring both electric and thermal management. Unique properties, in fact, can arise from accurate selection and processing of 2D fillers and their matrix. Here, we report an innovative family of nanocomposite membranes based on polyurethane (PU) and graphene nanoplatelets (GNPs), designed to improve thermal comfort in functional textiles. GNP particles were thoroughly characterized (through Raman, atomic force microscopy, high-resolution TEM, scanning electron microscope), and showed high crystallinity (I_D/I_G = 0.127), low thickness (D50 < 6–8 layers), and high lateral dimensions (D50 ≈ 3 μm). When GNPs were loaded (up to 10% wt/wt) into the PU matrix, their homogeneous dispersion resulted in an increase of the in-plane thermal conductivity of composite membranes up to 471%. The thermal dissipation of membranes, alone or coupled with cotton fabric, was further evaluated by means of an ad hoc system designed to simulate a human forearm. The results obtained provide a new strategy for the preparation of membranes suitable for technical textiles, with improved thermal comfort.     

Diphenyl-Methane Based Thyromimetic Inhibitors for Transthyretin Amyloidosis

Thyromimetics, whose physicochemical characteristics are analog to thyroid hormones (THs) and their derivatives, are promising candidates as novel therapeutics for neurodegenerative and metabolic pathologies. In particular, sobetirome (GC-1), one of the initial halogen-free thyromimetics, and newly synthesized IS25 and TG68, with optimized ADME-Tox profile, have recently attracted attention owing to their superior therapeutic benefits, selectivity, and enhanced permeability. Here, we further explored the functional capabilities of these thyromimetics to inhibit transthyretin (TTR) amyloidosis. TTR is a homotetrameric transporter protein for THs, yet it is also responsible for severe amyloid fibril formation, which is facilitated by tetramer dissociation into non-native monomers. By combining nuclear magnetic resonance (NMR) spectroscopy, computational simulation, and biochemical assays, we found that GC-1 and newly designed diphenyl-methane-based thyromimetics, namely IS25 and TG68, are TTR stabilizers and efficient suppressors of TTR aggregation. Based on these observations, we propose the novel potential of thyromimetics as a multi-functional therapeutic molecule for TTR-related pathologies, including neurodegenerative diseases.     

Thermodynamic modeling of hydrogen refueling for heavy-duty fuel cell buses and comparison with aggregated real data

The foreseen uptake of hydrogen mobility is a fundamental step towards the decarbonization of the transport sector. Under such premises, both refueling infrastructure and vehicles should be deployed together with improved refueling protocols. Several studies focus on refueling the light-duty vehicles with 10 kg_H2 up to 700 bar, however less known effort is reported for refueling heavy-duty vehicles with 30–40 kg_H2 at 350 bar. The present study illustrates the application of a lumped model to a fuel cell bus tank-to-tank refueling event, tailored upon the real data acquired in the 3Emotion Project. The evolution of the main refueling quantities, such as pressure, temperature, and mass flow, are predicted dynamically throughout the refueling process, as a function of the operating parameters, within the safety limits imposed by SAE J2601/2 technical standard. The results show to refuel the vehicle tank from half to full capacity with an Average Pressure Ramp Rate (APRR) equal to 0.03 MPa/s are needed about 10 min. Furthermore, it is found that the effect of varying the initial vehicle tank pressure is more significant than changing the ambient temperature on the refueling performances. In conclusion, the analysis of the effect of different APRR, from 0.03 to 0.1 MPa/s, indicate that is possible to safely reduce the duration of half-to-full refueling by 62% increasing the APRR value from 0.03 to 0.08 MPa/s.     

Quality-by-control of intensified continuous filtration-drying of active pharmaceutical ingredients

Continuous manufacturing and closed-loop quality control are emerging technologies that are pivotal for next-generation pharmaceutical modernization. We develop a process control framework for a continuous carousel for integrated filtration-drying of crystallization slurries. The proposed control system includes model-based monitoring and control routines, such as state estimation and real-time optimization, implemented in a hierarchical, three-layer quality-by-control (QbC) framework. We implement the control system in ContCarSim, a publicly available carousel simulator. We benchmark the proposed control system against simpler methods, comprising a reduced subset of the elements of the overall control system, and against open-loop operation (the current standard in pharmaceutical manufacturing). The proposed control system demonstrates superior performance in terms of higher consistency in product quality and increased productivity, proving the benefits of closed-loop control and of model-based techniques in pharmaceutical manufacturing. This study represents a step forward toward end-to-end continuous pharmaceutical processing, and in the evolution of quality-by-design toward quality-by-control.     

Coordination Environment of Cu(II) Ions Bound to N-Terminal Peptide Fragments of Angiogenin Protein

Angiogenin (Ang) is a potent angiogenic factor, strongly overexpressed in patients affected by different types of cancers. The specific Ang cellular receptors have not been identified, but it is known that Ang–actin interaction induces changes both in the cell cytoskeleton and in the extracellular matrix. Most in vitro studies use the recombinant form (r-Ang) instead of the form that is normally present in vivo (“wild-type”, wt-Ang). The first residue of r-Ang is a methionine, with a free amino group, whereas wt-Ang has a glutamic acid, whose amino group spontaneously cyclizes in the pyro-glutamate form. The Ang biological activity is influenced by copper ions. To elucidate the role of such a free amino group on the protein–copper binding, we scrutinized the copper(II) complexes with the peptide fragments Ang(1–17) and AcAng(1–17), which encompass the sequence 1–17 of angiogenin (QDNSRYTHFLTQHYDAK-NH₂), with free amino and acetylated N-terminus, respectively. Potentiometric, ultraviolet-visible (UV-vis), nuclear magnetic resonance (NMR) and circular dichroism (CD) studies demonstrate that the two peptides show a different metal coordination environment. Confocal microscopy imaging of neuroblastoma cells with the actin staining supports the spectroscopic results, with the finding of different responses in the cytoskeleton organization upon the interaction, in the presence or not of copper ions, with the free amino and the acetylated N-terminus peptides.     

Stochastic and recursive estimation of the hygro-thermo-chemical-mechanical parameters of concrete through Monte Carlo analysis and extended Kalman filter

Structural and Multidisciplinary Optimization - Hygro-thermo-chemical-mechanical models, used to determine the variations over time of temperature, relative humidity and shrinkage induced...     

Designing and upgrading model of pre-denitrification systems

This paper reports a three-substrate steady-state integrated model, whose unknowns are expressed in explicit terms once concentrations of nitrogen compounds in the effluent flow are fixed. The model can be applied both to design and to upgrade wastewater treatment plants. The model is also able to evaluate the flexibility of existing wastewater treatment plants, which represents the capacity of the system to operate under different working conditions caused by increases in influent load or reductions in effluent quality standards. In this case the admissible variation of influent load or effluent concentration can be measured using suitable dimensionless flexibility indexes.List of symbols Q influent flow [L³ T^–1] - R₁ sludge recycle flow ratio - R₂ aerated mixed liquor recycle flow ratio - V_D denitrification reactor volume [L³] - V_N nitrification reactor volume [L³] - S biodegradable organic substrate concentration [M L^–3] - N-NH₄ ammonia nitrogen concentration [M L^–3] - N-NO₃ nitrate nitrogen concentration [M L^–3] - N_tot total nitrogen concentration [M L^–3] - O₂ oxygen concentration in the nitrification reactor [M L^–3] - X_H heterotrophic biomass concentration [M L^–3] - X_AUT autotrophic biomass concentration [M L^–3] - maximum removal rate of biodegradable organic substrate for an assigned value of temperature [T^–1] - maximum removal rate of nitrate for an assigned value of temperature [T^–1] - maximum removal rate of ammonia nitrogen for assigned values of pH and temperature [T^–1] - _S removal rate of biodegradable organic substrate [T^–1] - _D removal rate of nitrate [T^–1] - _N removal rate of ammonia nitrogen [T^–1] - K_S saturation coefficient for biodegradable organic substrate [M L^–3] - K_D saturation coefficient for nitrate [M L^–3] - K_SD saturation coefficient for organic substrate in the denitrification kinetic [M L^–3] - K_N saturation coefficient for ammonia nitrogen [M L^–3] - saturation coefficient for oxygen [M L^–3] - Y_H yield coefficient for heterotrophic microorganisms in the biodegradable organic substrate removal process - Y_D yield coefficient for heterotrophic microorganisms in the nitrate nitrogen removal process - Y_AUT yield coefficient for autotrophic microorganisms in the ammonia nitrogen removal process - (X_H)_r heterotrophic biomass concentration in the recycle sludge [M L^–3] - (X_AUT)_r autotrophic biomass concentration in the recycle sludge [M L^–3] - biodegradable organic mass consumption for unitary nitrate nitrogen mass reduction in the denitrification reactor - nitrogen consumption in the biodegradable organic oxidation process by mean of heterotrophic biomass     

Groebner Bases and Distance of Cyclic Codes

 Recently some methods have been proposed to find the distance of cyclic codes using Gr?bner bases. We present a similar method, whose computational cost is significantly lower. Received: April 24, 2001; revised version: February 14, 2002