Low-cycle fatigue behavior of flexible 3D printed thermoplastic polyurethane blends for thermal energy storage/release applications

Thermal energy storage (TES) materials constituted by a microencapsulated paraffin having a melting temperature of 6°C and a thermoplastic polyurethane (TPU) matrix were prepared through fused deposition modeling. Scanning electron microscope (SEM) micrographs demonstrated that the microcapsules were homogeneously distributed within the matrix, with a rather good adhesion within the layers of 3D printed specimens, even at elevated concentrations of microcapsules. The presence of paraffin capsules having a rigid polymer shell lead to a stiffness increase, associated to a decrease in the stress and in the strain at break. Tensile and compressive low-cycles fatigue tests showed that the presence of microcapsules negatively affected the fatigue resistance of the samples, and that the main part of the damage occurred in the first fatigue cycles. After the first 10 loading cycles at 50% of the stress at break, a decrease in the elastic modulus ranging from 60% for neat TPU to 80% for composite materials was detected. This decrease reached 40% of the original value at 90% of the stress at break after 10 cycles. Differential scanning calorimetry tests on specimens after fatigue loading highlighted a substantial retention of the original TES capability, in the range of 80%–90% of the pristine value, even after 1000 cycles, indicating that the integrity of the capsules was maintained and that the propagation of damage during fatigue tests took probably place within the surrounding polymer matrix. It could be therefore concluded that it is possible to apply the developed blends in applications where the materials are subjected to cyclic stresses, both in tensile and compressive mode.     

Vacuum impregnation of chitosan‐based edible coating in minimally processed pumpkin

The goal of this research was to evaluate the use of vacuum impregnation (VI) and soaking techniques (ST) in the application of edible coatings of chitosan and chitosan + lauric acid to minimally processed pumpkins (MPP). The vacuum impregnation method led to greater component incorporation (5.9% and 1.75%, respectively) in the pumpkins when compared to soaking and consequently the formation of more uniform, thicker coatings (25.6 and 22.3 μm, respectively). However, VI caused greater changes in pH, acidity, colour and firmness. Relating to water content and carotenoid content, noncoated pumpkins presented greater losses during the storage period, regardless of impregnation method. The pumpkins with edible coatings, regardless of method, presented lower numbers of psychrotrophic micro‐organisms and coliforms during the storage period. Therefore, soaking was considered the best method for the application of chitosan‐based edible coatings to minimally processed pumpkins, as it led to smaller changes in the properties of the product.     

EGGS: Sparsity-Specific Code Generation

Sparse matrix computations are among the most important computational patterns, commonly used in geometry processing, physical simulation, graph algorithms, and other situations where sparse data arises. In many cases, the structure of a sparse matrix is known a priori, but the values may change or depend on inputs to the algorithm. We propose a new methodology for compile-time specialization of algorithms relying on mixing sparse and dense linear algebra operations, using an extension to the widely-used open source Eigen package. In contrast to library approaches optimizing individual building blocks of a computation (such as sparse matrix product), we generate reusable sparsity-specific implementations for a given algorithm, utilizing vector intrinsics and reducing unnecessary scanning through matrix structures. We demonstrate the effectiveness of our technique on a benchmark of artificial expressions to quantitatively evaluate the benefit of our approach over the state-of-the-art library Intel MKL. To further demonstrate the practical applicability of our technique we show that our technique can improve performance, with minimal code changes, for mesh smoothing, mesh parametrization, volumetric deformation, optical flow, and computation of the Laplace operator.     

Hierarchical Coherent Phonons in a Superatomic Semiconductor

The coupling of phonons to electrons and other phonons plays a defining role in material properties, such as charge and energy transport, light emission, and superconductivity. In atomic solids, phonons are delocalized over the 3D lattice, in contrast to molecular solids where localized vibrations dominate. Here, a hierarchical semiconductor that expands the phonon space by combining localized 0D modes with delocalized 2D and 3D modes is described. This material consists of superatomic building blocks (Re₆Se₈) covalently linked into 2D sheets that are stacked into a layered van der Waals lattice. Using transient reflectance spectroscopy, three types of coherent phonons are identified: localized 0D breathing modes of isolated superatom, 2D synchronized twisting of superatoms in layers, and 3D acoustic interlayer deformation. These phonons are coupled to the electronic degrees of freedom to varying extents. The presence of local phonon modes in an extended crystal opens the door to controlling material properties from hierarchical phonon engineering.     

Hybridizing adaptive large neighborhood search with kernel search: a new solution approach for the nurse routing problem with incompatible services and minimum demand

The average age of the population has grown steadily in recent decades along with the number of people suffering from chronic diseases and asking for treatments. Hospital care is expensive and often unsafe, especially for older individuals. This is particularly true during pandemics as the recent SARS-CoV-2. Hospitalization at home has become a valuable alternative to face efficiently a huge increase in treatment requests while guaranteeing a high quality of service and lower risk to fragile patients. This new model of care requires the redefinition of health services organization and the optimization of scarce resources (e.g., available nurses). In this paper, we study a Nurse Routing Problem that tries to find a good balance between hospital costs reduction and the well-being of patients, also considering realistic operational restrictions like maximum working times for the nurses and possible incompatibilities between services jointly provided to the same patient. We first propose a Mixed Integer Linear Programming formulation for the problem and use some valid inequalities to strengthen it. A simple branch-and-cut algorithm is proposed and validated to derive ground benchmarks. In addition, to efficiently solve the problem, we develop an Adaptive Large Neighborhood Search hybridized with a Kernel Search and validate its performance over a large set of different realistic working scenarios. Computational tests show how our matheuristic approach manages to find good solutions in a reasonable amount of time even in the most difficult settings. Finally, some interesting managerial insights are discussed through an economic analysis of the operating context.     

Potential to retrofit existing small-scale gasifiers through steam gasification of biomass residues for hydrogen and biofuels production

This work investigates the opportunity of retrofitting existing small-scale gasifiers shifting from combined heat and power (CHP) to hydrogen and biofuels production, using steam and biomass residues (woodchips, vineyard pruning and bark). The experiments were carried out in a batch reactor at 700 °C and 800 °C and at different steam flow (SF) rates (0.04 g/min and 0.20 g/min). The composition of the producer gas is in the range of 46–70 % H₂, 9–29 % CO, 12–27 % CO₂, and 2–6 % CH₄. A producer gas specific production factor of approx. 10 NL_pg/g_char can be achieved when the lower SFs are used, which allows to provide 80 % of the hydrogen concentration required for biomethanation and MeOH synthesis. As for FT synthesis, an optimal H₂/CO ratio of approx. 2 can be achieved. The results of this work provide further evidence towards the feasibility of hydrogen and biofuels generation from residual biomass through steam gasification.     

2-Phenyloxazole-4-carboxamide as a Scaffold for Selective Inhibition of Human Monoamine Oxidase B

A series of 2-phenyloxazoles bearing an amide group at position 4 were designed and synthesized for evaluation as potential inhibitors of human recombinant monoamine oxidases (hrMAOs). Results of kinetics experiments demonstrated that all compounds behave as competitive MAO inhibitors, with good selectivity toward the MAO-B isoform. The most potent and selective derivatives are characterized by inhibition constant (K_i) values in the sub-micromolar range and a good selectivity index (K_{i MAO-A}/K_{i MAO-B}>50). Some derivatives were also found to be able to inhibit MAO activity in nerve growth factor (NGF)-differentiated PC12 cells, taken as a model of neuronal cells. In particular, 2-(2-hydroxyphenyl)-N-phenyloxazole-4-carboxamide (compound 4 a ) may be a promising new scaffold, exerting the highest selectivity and inhibitory effect toward MAOs in NGF-differentiated PC12 cell lysates, without compromising cell viability. Molecular docking analysis allowed a rationalization of the experimentally observed binding affinity and selectivity.     

Landscape dynamics of Mediterranean montane grasslands over 60 years and implications for habitats conservation. A case study in the northern Apennines (Italy)

Widespread trends of abandonment have strongly affected Mediterranean mountains after the Second World War, triggering spontaneous recolonisation of forests. A diachronic analysis of the landscape in a Natura 2000 site (Tuscany, Italy) was carried out using digital aerial photographs (1954, 2013) and a GIS-based methodology, focusing on territories above 1300 m a.s.l. The detected variations of total areas, patch shape, patch dimensions and selected metrics showed a notable shift of the vegetation towards woody types and a drastic reduction of open grasslands, some with high conservation value, accompanied by a strong increase in patch number, surface and edge. A decrease of SDI and SEI diversity indices was also observed. Considering that fragmentation is one of the main causes threatening habitats and species, our results point out a clear necessity for a monitoring programme and suitable actions aimed at improving the status of biodiversity-rich montane grasslands.     

A2B Adenosine Receptors: When Outsiders May Become an Attractive Target to Treat Brain Ischemia or Demyelination

Adenosine is a signaling molecule, which, by activating its receptors, acts as an important player after cerebral ischemia. Here, we review data in the literature describing A_2BR-mediated effects in models of cerebral ischemia obtained in vivo by the occlusion of the middle cerebral artery (MCAo) or in vitro by oxygen-glucose deprivation (OGD) in hippocampal slices. Adenosine plays an apparently contradictory role in this receptor subtype depending on whether it is activated on neuro-glial cells or peripheral blood vessels and/or inflammatory cells after ischemia. Indeed, A_2BRs participate in the early glutamate-mediated excitotoxicity responsible for neuronal and synaptic loss in the CA1 hippocampus. On the contrary, later after ischemia, the same receptors have a protective role in tissue damage and functional impairments, reducing inflammatory cell infiltration and neuroinflammation by central and/or peripheral mechanisms. Of note, demyelination following brain ischemia, or autoimmune neuroinflammatory reactions, are also profoundly affected by A_2BRs since they are expressed by oligodendroglia where their activation inhibits cell maturation and expression of myelin-related proteins. In conclusion, data in the literature indicate the A_2BRs as putative therapeutic targets for the still unmet treatment of stroke or demyelinating diseases.