Biological Effects of 25 to 150 GHz Radiation After In Vitro Exposure of Human Fibroblasts: a Comparison of Experimental Results

In this paper, we present a comprehensive discussion of the results obtained after in vitro exposure of human fetal fibroblasts and human adult fibroblasts to pulsed radiation in a wide band between 100 and 150 GHz and to continuous wave radiation at 25 GHz. In order to assess potential effects of exposure, the genome integrity, cell cycle, cytological ultrastructure, and proteins expression were evaluated.     

In Situ Production of Biofunctionalized Few‐Layer Defect‐Free Microsheets of Graphene

Biological interfacing of graphene has become crucial to improve its biocompatibility, dispersability, and selectivity. However, biofunctionalization of graphene without yielding defects in its sp²‐carbon lattice is a major challenge. Here, a process is set out for biofunctionalized defect‐free graphene synthesis through the liquid phase ultrasonic exfoliation of raw graphitic material assisted by the self‐assembling fungal hydrophobin Vmh2. This protein (extracted from the edible fungus Pleurotus ostreatus) is endowed with peculiar physicochemical properties, exceptional stability, and versatility. The unique properties of Vmh2 and, above all, its superior hydrophobicity, and stability allow to obtain a highly concentrated (≈440–510 μg mL^?1) and stable exfoliated material (ζ‐potential, +40/+70 mV). In addition controlled centrifugation enables the selection of biofunctionalized few‐layer defect‐free micrographene flakes, as assessed by Raman spectroscopy, atomic force microscopy, scanning electron microscopy, and electrophoretic mobility. This biofunctionalized product represents a high value added material for the emerging applications of graphene in the biotechnological field such as sensing, nanomedicine, and bioelectronics technologies.     

Peptide‐Passivated Lead Halide Perovskite Nanocrystals Based on Synergistic Effect between Amino and Carboxylic Functional Groups

A new strategy has been developed using peptides with amino and carboxylic functional groups as passivating ligands to produce methyl ammonium lead bromide (CH₃NH₃PbBr₃) perovskite nanocrystals (PNCs) with excellent optical properties. The well‐passivated PNCs can only be obtained when both amino and carboxylic groups are involved, and this is attributed to the protonation reaction between ? NH₂ and ? COOH that is essential for successful passivation of the PNCs. To better understand this synergistic effect, peptides with different lengths have been studied and compared. Due to the polar nature of peptides, peptide‐passivated PNCs (denoted as PNCs_peptide) aggregate and precipitate from nonpolar toluene solvent, resulting in a high product yield (≈44%). Furthermore, the size of PNCs_peptide can be varied from ≈3.9 to 8.6 nm by adjusting the concentration of the peptide, resulting in tunable optical properties due to the quantum confinement effect. In addition, CsPbBr₃ PNCs are also synthesized with peptides as capping ligands, further demonstrating the generality and versatility of this strategy, which is important for generating high quality PNCs for photonics applications including light‐emitting diodes, optical sensing, and imaging.     

Highly Tunable Syngas Product Ratios Enabled by Novel Nanoscale Hybrid Electrolytes Designed for Combined CO2 Capture and Electrochemical Conversion

Coupling renewable energy with the electrochemical conversion of CO₂ to chemicals and fuels has been proposed as a strategy to achieve a new circular carbon economy and help mitigate the effects of anthropogenic CO₂ emissions. Liquid-like Nanoparticle Organic Hybrid Materials (NOHMs) are composed of polymers tethered to nanoparticles and are previously explored as CO₂ capture materials and electrolyte additives. In this study, two types of aqueous NOHM-based electrolytes are prepared to explore the effect of CO₂ binding energy (i.e., chemisorption versus physisorption) on CO₂ electroreduction over a silver nanoparticle catalyst for syngas production. Poly(ethylenimine) (PEI) and Jeffamine M2070 (HPE) are ionically tethered to SiO₂ nanoparticles to form the amine-containing NOHM-I-PEI and ether-containing NOHM-I-HPE, respectively. At less negative cathode potentials, PEI and NOHM-I-PEI-based electrolytes produce CO at higher rates than 0.1 molal. KHCO₃ due to favorable catalyst-electrolyte interactions. Whereas at more negative potentials, H₂ production is favored because of the carbamate electrochemical inactivity. Conversely, HPE and NOHM-I-HPE-based electrolytes display poor CO₂ reduction performance at less negative potentials. At more negative potentials, their performance approached that of 0.1 molal. KHCO₃, highlighting how the polymer functional groups of NOHMs can be strategically selected to produce value-added products from CO₂ with highly tunable compositions.     

Accuracy of q-space related parameters in MRI: simulations and phantom measurements

The accuracy of q-space measurements was evaluated at a 3.0-T clinical magnetic resonance imaging (MRI) scanner, as compared with a 4.7-T nuclear magnetic resonance (NMR) spectrometer. Measurements were performed using a stimulated-echo pulse-sequence on n-decane as well as on polyethylene glycol (PEG) mixed with different concentrations of water, in order to obtain bi-exponential signal decay curves. The diffusion coefficients as well as the modelled diffusional kurtosis K(fit) were obtained from the signal decay curve, while the full-width at half-maximum (FWHM) and the diffusional kurtosis K were obtained from the displacement distribution. Simulations of restricted diffusion, under conditions similar to those obtainable with a clinical MRI scanner, were carried out assuming various degrees of violation of the short gradient pulse (SGP) condition and of the long diffusion time limit. The results indicated that an MRI system can not be used for quantification of structural sizes less than about 10 microm by means of FWHM since the parameter underestimates the confinements due to violation of the SGP condition. However, FWHM can still be used as an important contrast parameter. The obtained kurtosis values were lower than expected from theory and the results showed that care must be taken when interpreting a kurtosis estimate deviating from zero.     

Conversion of n-heptane over different catalysts: Effect of catalyst-to-oil ratio and temperature

Catalytic cracking of n–heptane was investigated over various catalysts including ZSM-5, MCM-41, USY and mordenite. The influence of reaction temperature and catalyst-to-oil ratio was investigated in the case of ZSM-5 as more favorable catalyst in terms of conversion and light olefins yield. The highest n-heptane conversion of 97.3 wt.% was achieved over USY zeolite. Both conversion and olefin selectivity were increased by temperature over ZSM-5 zeolite. Increasing catalyst-to-oil ratio enhanced conversion with no significant changes in olefins selectivity. The highest olefin production was achieved over ZSM-5 zeolite in catalyst-to-oil ratios of 1.5 and 3.0 (g/g) at 550°C.     

Electro‐Drawn Drug‐Loaded Biodegradable Polymer Microneedles as a Viable Route to Hypodermic Injection

Hypodermic needle injection is still the most common method of drug delivery despite its numerous limitations and drawbacks, such as pain, one‐shot administration, and risk of infection. Seeking a viable, safe, and pain‐free alternative to the over 16 billion injections per year has therefore become a top priority for our modern technological society. Here, a system that uses a pyroelectric cartridge in lieu of the syringe piston as a potential solution is discussed. Upon stimulation, the cartridge electro‐draws, at room temperature, an array of drug‐encapsulated, biodegradable polymer microneedles, able to deliver into hypodermic tissue both hydrophobic and hydrophilic bioactive agents, according to a predefined chrono‐programme. This mould‐free and contact‐free method permits the fabrication of biodegradable polymer microneedles into a ready‐to‐use configuration. In fact, they are formed on a flexible substrate/holder by drawing them directly from drop reservoirs, using a controlled electro‐hydrodynamic force. Tests of insertion are performed and discussed in order to demonstrate the possibility to prepare microneedles with suitable geometric and mechanical properties using this method.     

Encapsulation of Noble Metal Nanoparticles through Seeded Emulsion Polymerization as Highly Stable Plasmonic Systems

The implementation of plasmonic nanoparticles in vivo remains hindered by important limitations such as biocompatibility, solubility in biological fluids, and physiological stability. A general and versatile protocol is presented, based on seeded emulsion polymerization, for the controlled encapsulation of gold and silver nanoparticles. This procedure enables the encapsulation of single nanoparticles as well as nanoparticle clusters inside a protecting polymer shell. Specifically, the efficient coating of nanoparticles of both metals is demonstrated, with final dimensions ranging between 50 and 200 nm, i.e., sizes of interest for bio‐applications. Such hybrid nanocomposites display extraordinary stability in high ionic strength and oxidizing environments, along with high cellular uptake, and low cytotoxicity. Overall, the prepared nanostructures are promising candidates for plasmonic applications under biologically relevant conditions.     

Arithmetic Optimization with Ensemble Deep Transfer Learning BasedMelanoma Classification

Melanoma is a skin disease with high mortality rate while early diagnoses of the disease can increase the survival chances of patients. It is challenging to automatically diagnose melanoma from dermoscopic skin samples. Computer-Aided Diagnostic (CAD) tool saves time and effort in diagnosing melanoma compared to existing medical approaches. In this background, there is a need exists to design an automated classification model for melanoma that can utilize deep and rich feature datasets of an image for disease classification. The current study develops an Intelligent Arithmetic Optimization with Ensemble Deep Transfer Learning Based Melanoma Classification (IAOEDTT-MC) model. The proposed IAOEDTT-MC model focuses on identification and classification of melanoma from dermoscopic images. To accomplish this, IAOEDTT-MC model applies image preprocessing at the initial stage in which Gabor Filtering (GF) technique is utilized. In addition, U-Net segmentation approach is employed to segment the lesion regions in dermoscopic images. Besides, an ensemble of DL models including ResNet50 and ElasticNet models is applied in this study. Moreover, AO algorithm with Gated Recurrent Unit (GRU) method is utilized for identification and classification of melanoma. The proposed IAOEDTT-MC method was experimentally validated with the help of benchmark datasets and the proposed model attained maximum accuracy of 92.09% on ISIC 2017 dataset.     

<Emphasis Type="Italic">ℓ</Emphasis><Subscript>1</Subscript>-penalization for mixture regression models

We consider a finite mixture of regressions (FMR) model for high-dimensional inhomogeneous data where the number of covariates may be much larger than sample size. We propose an ℓ ₁-penalized maximum likelihood estimator in an appropriate parameterization. This kind of estimation belongs to a class of problems where optimization and theory for non-convex functions is needed. This distinguishes itself very clearly from high-dimensional estimation with convex loss- or objective functions as, for example, with the Lasso in linear or generalized linear models. Mixture models represent a prime and important example where non-convexity arises.