Anisotropic infrared light emission from quasi-1D layered TiS\u3csub\u3e3\u3c/sub\u3e

\u3cp\u3eAtomically thin semiconductors hold great potential for nanoscale photonic and optoelectronic devices because of their strong light absorption and emission. Despite progress, their application in integrated photonics is hindered particularly by a lack of stable layered semiconductors emitting in the infrared part of the electromagnetic spectrum. Here we show that titanium trisulfide (TiS\u3csub\u3e3\u3c/sub\u3e), a layered van der Waals material consisting of quasi-1D chains, emits near infrared light centered around 0.91 eV (1360 nm). Its photoluminescence exhibits linear polarization anisotropy and an emission lifetime of 210 ps. At low temperature, we distinguish two spectral contributions with opposite linear polarizations attributed to excitons and defects. Moreover, the dependence on excitation power and temperature suggests that free and bound excitons dominate the excitonic emission at high and low temperatures, respectively. Our results demonstrate the promising properties of TiS\u3csub\u3e3\u3c/sub\u3e as a stable semiconductor for optoelectronic and nanophotonic devices operating at telecommunication wavelengths. \u3c/p\u3

CD44-targeted vesicles encapsulating granzyme B as artificial killer cells for potent inhibition of human multiple myeloma in mice

\u3cp\u3eMultiple myeloma (MM) is a malignant blood cancer homing in bone marrow that is particularly hard to treat. The effective treatment for MM shall be not only MM-selective but also capable of homing to bone marrow. Herein, we report on hyaluronic acid-directed reduction-responsive chimaeric polymersomes encapsulating a key player in the NK cells, granzyme B (HA-RCP-GrB) as an artificial killer cell for targeted protein therapy of MM. Interestingly, HA-RCP-GrB displayed high MM-targetability and anti-MM activity with a remarkably low IC\u3csub\u3e50\u3c/sub\u3e of 8.1 nM toward CD44 overexpressing LP1 human MM cells. The in vivo biodistribution studies using Cy5-labeled cytochrome C as a model protein demonstrated significantly enhanced accumulation of HA-RCP in the subcutaneous LP1 tumor as well as in the bone marrow of orthotopic LP1 MM model compared with the non-targeted RCP counterparts, confirming that HA-RCP possesses MM-selectivity and is able to deliver proteins to the bone marrow. In accordance, HA-RCP-GrB exerted significantly better suppression of subcutaneous LP1 tumor than the non-targeted RCP-GrB. More interestingly, in the orthotopic LP1 MM-bearing mice, HA-RCP-GrB led to significant survival benefits and less body weight loss over PBS and RCP-GrB. μCT analyses, H&E and TRAP staining revealed that mice treated with HA-RCP-GrB had greatly reduced osteolysis and proliferation of atypical plasma cells in the bone marrow. HA-RCP-GrB has emerged as a novel and effective treatment for multiple myeloma.\u3c/p\u3

Surfing on fitness landscapes: a boost on optimization by Fourier surrogate modeling

Surfing in rough waters is not always as fun as wave riding the “big one”. Similarly, in optimization problems, fitness landscapes with a huge number of local optima make the search for the global optimum a hard and generally annoying game. Computational Intelligence optimization metaheuristics use a set of individuals that “surf” across the fitness landscape, sharing and exploiting pieces of information about local fitness values in a joint effort to find out the global optimum. In this context, we designed surF, a novel surrogate modeling technique that leverages the discrete Fourier transform to generate a smoother, and possibly easier to explore, fitness landscape. The rationale behind this idea is that filtering out the high frequencies of the fitness function and keeping only its partial information (i.e., the low frequencies) can actually be beneficial in the optimization process. We prove our theory by combining surF with a settings free variant of Particle Swarm Optimization (PSO) based on Fuzzy Logic, called Fuzzy Self-Tuning PSO. Specifically, we introduce a new algorithm, named F3ST-PSO, which performs a preliminary exploration on the surrogate model followed by a second optimization using the actual fitness function. We show that F3ST-PSO can lead to improved performances, notably using the same budget of fitness evaluations

Computational modeling for cardiovascular tissue engineering:the importance of including cell behavior in growth and remodeling algorithms

\u3cp\u3eUnderstanding cardiovascular growth and remodeling (G&R) is fundamental for designing robust cardiovascular tissue engineering strategies, which enable synthetic or biological scaffolds to transform into healthy living tissues after implantation. Computational modeling, particularly when integrated with experimental research, is key for advancing our understanding, predicting the in vivo evolution of engineered tissues, and efficiently optimizing scaffold designs. As cells are ultimately the drivers of G&R and known to change their behavior in response to mechanical cues, increasing efforts are currently undertaken to capture (mechano-mediated) cell behavior in computational models. In this selective review, we highlight some recent examples that are relevant in the context of cardiovascular tissue engineering and discuss the current and future biological and computational challenges for modeling cell-mediated G&R.\u3c/p\u3

Scaling method of CFD-DEM simulations for gas-solid flows in risers

\u3cp\u3eIn this paper a scaling method is proposed for scaling down the prohibitively large number of particles in CFD-DEM simulations for modeling large systems such as circulating fluidized beds. Both the gas and the particle properties are scaled in this method, and a detailed comparison among alternative mapping strategies is performed by scaling both the computational grid size and the riser depth. A series of CFD-DEM simulations has been performed for a pseudo-2D CFB riser to enable a detailed comparison with experimental data. By applying the scaling method, the hydrodynamic flow behavior could be well predicted and cluster characteristics, such as cluster velocity and cluster holdups agreed well with the experimental data. For a full validation of the scaling method, four mapping conditions with different ratios of the grid size and particle volume and of modified ratio of riser depth to particle size were analyzed. The results show that in addition to hydrodynamic scaling of the particle and fluid properties, scaling of the dimensions for the interphase mapping is also necessary.\u3c/p\u3

Process design for green hydrogen production

\u3cp\u3eA membrane assisted process for green hydrogen production from a bioethanol derived feedstock is here developed and evaluated, starting from the conventional Steam Methane Reforming (SMR) process. Such a process is suitable for centralized hydrogen production, and is here analyzed for a large-scale H\u3csub\u3e2\u3c/sub\u3e production unit with the capacity of 40.000 Nm\u3csup\u3e3\u3c/sup\u3e/h. The basic Steam Ethanol Reforming (SER) process scheme is modified in a membrane assisted process by integrating the Pd-membrane separation steps in the most suitable reaction steps. The membrane assisted process, configured in three alternative architectures (Open architecture, Membrane Reactor and Hybrid architecture) was evaluated in terms of efficiencies and hydrogen yields, obtaining a clear indication of improved process performance. The alternative membrane assisted process architectures are compared to the basic SER process and to the benchmark SMR process fed by natural gas, for an overall comparative assessment of the efficiency and specific CO\u3csub\u3e2\u3c/sub\u3e emissions and for an economic analysis based on the operating expenditures.\u3c/p\u3

Atomic layer deposition of aluminum phosphate using AlMe3, PO(OMe)3 and O2 plasma: film growth and surface reactions

High purity, uniform, and conformal aluminum phosphate (AlPxOy) thin films were deposited by atomic layer deposition (ALD) between 25 and 300 °C using supercycles consisting of (i) PO(OMe)3 dosing combined with O2 plasma exposure and (ii) AlMe3 dosing followed by O2 plasma exposure. In situ spectroscopic ellipsometry and mass spectrometry were applied to demonstrate the ALD self-limiting behavior and to gain insight into the surface reactions during the precursor and coreactant exposures, respectively. Compared to earlier reported AlPxOy ALD studies using H2O and O3 as coreactants or without using coreactans, the use of an oxygen plasma generally leads to higher growth per cycle values and promotes phosphorus incorporation in the film. Specifically, when using a 1:1 POx:Al2O3 cycle ratio and a substrate temperature of 150 °C, the growth per supercycle is found to be 1.8 Å. The [P]:[Al] atomic ratio for this process is approximately 0.5 (∼AlP0.5O2.9) and can be tailored by changing the ratio between the two cycles or the substrate temperature. In literature reports where the same aluminum precursor was used, the [P]:[Al] atomic ratio was limited to 0.2 or a very high number of phosphorus cycles was needed in order to increase the phosphorus content. Instead, we demonstrate deposition of films with a composition close to AlPO4 by using a 2:1 POx:Al2O3 cycle ratio. The limited incorporation of P in the film is suspected to derive from the steric hindrance of the relatively bulky phosphorus precursor. Mass spectrometry suggests that the PO(OMe)3 precursor chemisorbs on the surface without the release of reaction products into the gas phase, whereas Al(Me)3 already undergoes methyl ligand abstraction upon chemisorption.\u3cbr/\u3

The relationship between job demands, job resources and teachers’ professional learning:is it explained by self-determination theory?

\u3cp\u3eAlthough teachers’ commitment to continuous professional learning is crucial for high quality education, research shows that this learning cannot be taken for granted. To better understand how teachers’ learning at work can be supported, this study investigates how effects of job demands (i.e. work pressure and emotional pressure) and job resources (i.e. task autonomy, transformational leadership, and collegial support) on teachers’ learning commitment (i.e. learning frequency and engagement) can be explained by basic psychological need satisfaction and autonomous motivation, as posited by self-determination theory. At two occasions, approximately one year apart, data was collected in a sample of 678 (T1) and 536 (T2) Dutch secondary school teachers. Structural equation models showed the consecutive positive longitudinal relationships between teachers’ experience of job resources, basic psychological need satisfaction, autonomous motivation, and commitment to professional learning. Job demands were not related to basic need satisfaction over and above the effects of job resources. Implications for how self-determination theory and the job demands resources model can mutually inform each other are discussed. In addition, implications for stimulating teachers’ professional learning in practice are provided.\u3c/p\u3