Charge Density Based Small Signal Modeling for InSb/AlInSb Asymmetric Double Gate Silicon Substrate HEMT for High Frequency Applications

Silicon - This paper proposes the Asymmetric Double Gate Silicon Substrate HEMT (ADG-Si-HEMT) to study the carrier concentration and intrinsic small signal parameters of the InSb/AlInSb silicon...     

Assessment of antimicrobial activity of melittin encapsulated in bicontinuous microemulsions prepared using renewable oils

The objective of this study is to demonstrate that melittin, a well-studied antimicrobial peptide (AMP), can be solubilized in an active form in bicontinuous microemulsions (BMEs) that employ biocompatible oils. The systems investigated consisted of Winsor-III and -IV BME phases composed of Water/Aerosol-OT (AOT)/Polysorbate 85/isopropyl myristate and a Winsor-IV BME employing Polysorbate 80 and limonene. We found that melittin resided in an α-helix-rich configuration and was in an apolar environment for the AOT/Polysorbate 85 Winsor-III system, suggesting that melittin interacted with the surfactant monolayer and was in an active conformation. An apolar environment was also detected for melittin in the two Winsor-IV systems, but to a lesser extent than the Winsor-III system. Small-angle X-ray scattering analysis indicated that melittin at a concentration of 1.0 g/L_aq in the aqueous subphase of the Winsor-IV systems led to the greatest impact on the BME structure (e.g., decrease of quasi-periodic repeat distance and correlation length and induction of interfacial fluidity). The antimicrobial activity of the Polysorbate 80 Winsor-IV system was evaluated against several bacteria prominent in chronic wounds and surgical site infections (SSIs). Melittin-free BMEs inhibited the growth of all tested bacteria due to its oil, limonene, while the inclusion of 1.0 g/L_aq of melittin in the BMEs enhanced the activity against several bacteria. A further increase of melittin concentration in the BMEs had no further enhancement. These results demonstrate the potential utility of BMEs as a delivery platform for AMPs and other hydrophilic and lipophilic drugs to inhibit antibiotic-resistant microorganisms in chronic wounds and SSIs.     

Upconversion of NaYF4: Yb,Er Nanoparticles Co-doped with Zr 4+ for Magnetic Phase Transition and Biomedical Imaging Applications

Tracking of cancer cells and cytotoxicity of normal tissue are the leading problem in cancer treatment. The magnetic and fluorescent multifunctional particles evolve as an emerging alternative for future target recognition. The ferromagnetic materials potentially treat the defects in the gene. Hence, ferromagnetic materials are the best for the treatment of cancer using gene therapy. Here, β-NaYF₄: Yb, Er compounds doped with 10%, 20% and 30% Zirconium (Zr) are prepared through hydrothermal technique. Citrate itself is a highly biocompatible surface ligand that labels the imaging probe. The X-ray diffraction analysis is evident for transforming hexagonal to cubic phase via Zr doping in NaYF₄: Yb, Er compounds. The electron microscopic images identify the hexagonal plates. This compound can emit visible light in response to infrared (IR) light irradiation. Especially β-NaYF₄: Yb, Er, and 10% of Zr, Yb, Er tridoped NaYF₄ compounds show enhanced red emission exploited in bioimaging applications. Insignificantly, 30% of Zr, Yb, Er tridoped NaYF₄ concentration exhibit hexagonal and dominating cubic (α) phase, could decrease red emissions intensity and magnetisation value. This Zr material reveals peculiar magnetic properties, especially ferromagnetism at a lower magnetic field and produces paramagnetism at a higher magnetic field. Here, 10–20% Zr, Yb, Er tridoped NaYF₄ concentrations exhibit better magnetic properties. The resultant compound is viable for the VERO cells.

     

An intelligent hierarchical residual attention learning-based conjoined twin neural network for Alzheimer's stage detection and prediction

Alzheimer's disorder (AD) causes permanent impairment in the brain's memory of the cellular system, leading to the initiation of dementia. Earlier detection of Alzheimer's disease in the initial stages is challenging for researchers. Deep learning and machine learning-based techniques can help resolve many issues associated with brain imaging exploration. Brain MR Images (Brain-MRI) are used to detect Alzheimer's in computable research work. To correctly categorize the stages of Alzheimer's disease, discriminative features need to be extracted from the MR images. Recently, many studies have used deep learning methods for the early detection of this disorder. However, overfitting degrades the deep learning method's performance because the dataset's selection images are smaller and imbalanced. Some studies could not reach more discriminative and effectual attention-aware features for Alzheimer's stage classification to increase the model performance. In this paper, we develop a novel hierarchical residual attention learning-inspired multistage conjoined twin network (HRAL-CTNN) to classify the stages of Alzheimer's. We used augmentation approaches to scale insufficient and imbalanced data. The HRAL-CTNN is efficiently overcoming the issues of not obtaining efficient attention-aware and generative features for Alzheimer's stage classification. The proposed model solved the problem of redundant features by extracting attentive discriminant features, and scaling imbalance data by data augmentation, after that training and validation using HRAL-CTNN. The execution of this proposed work has been performed on the ADNI MRI dataset. This work achieved outstanding accuracy of 99.97 $\pm$ 0.01% and F1 score of 99.30 $\pm$ 0.02% for Alzheimer's stage classification. This model proposed by our group outperformed the existing related studies in terms of the model's performance score.     

A High Capacity Preamble Sequence for Random Access in 5G IoT Networks: Design and Analysis

International Journal of Wireless Information Networks - 5G NR aims to enable the high density of Internet of Things (IoT), around one million $$(10^{6})$$ connections per square kilometer, through...     

Synergistic Excited State Involved Catalytic Reduction of (NH3-trz)[Fe(dipic)2] Complex by SnO2/TiO2 Nanocomposite

In this study, cost-effective, environmentally friendly well-fabricated SnO₂/TiO₂ nanocomposite synthesized via hydrothermal route and the photocatalytic activity was validated using the (NH₃-trz)[Fe(dipic)₂] complex under ultra-violet illumination. The structural features of (NH₃-trz)[Fe(dipic)₂] complex and catalysts were systematically examined by various characteristics. The photoreactivity of the model compound (NH₃-trz)[Fe(dipic)₂] in water/binary solvent systems was investigated. The rate of photoreaction (k) of nanocomposite (0.1432 s^?1) is higher than the SnO₂ (0.0373 s^?1) and TiO₂ (0.1422 s^?1) in H₂O:PrⁱOH (70:30%) than the rest of the solvents system. The pathways, mechanistic feature of accumulated reactive species on nanocomposite to induce adherent [Fe(dipic)₂]^? anion and photo-reductive products were studied.

Graphical Abstract