Beta cyclodextrin conjugated AuFe3O4 Janus nanoparticles with enhanced chemo-photothermal therapy performance.

The strategic integration of multi-functionalities within a singular nanoplatform has received growing attention for enhancing treatment efficacy, particularly in chemo-photothermal therapy. This study introduces a comprehensive concept of Janus nanoparticles (JNPs) composed of Au and Fe3O4 nanostructures intricately bonded with ß-cyclodextrins (ß-CD) to encapsulate 5-Fluorouracil (5-FU) and Ibuprofen (IBU). This strategic structure is engineered to exploit the synergistic effects of chemo-photothermal therapy, underscored by their exceptional biocompatibility and photothermal conversion efficiency (∼32.88 %). Furthermore, these ß-CD-conjugated JNPs enhance photodynamic therapy by generating singlet oxygen (1O2) species, offering a multi-modality approach to cancer eradication. Computer simulation results were in good agreement with in vitro and in vivo assays. Through these studies, we were able to prove the improved tumor ablation ability of the drug-loaded ß-CD-conjugated JNPs, without inducing adverse effects in tumor-bearing nude mice. The findings underscore a formidable tumor ablation potency of ß-CD-conjugated Au-Fe3O4 JNPs, heralding a new era in achieving nuanced, highly effective, and side-effect-free cancer treatment modalities. STATEMENT OF SIGNIFICANCE: The emergence of multifunctional nanoparticles marks a pivotal stride in cancer therapy research. This investigation unveils Janus nanoparticles (JNPs) amalgamating gold (Au), iron oxide (Fe3O4), and ß-cyclodextrins (ß-CD), encapsulating 5-Fluorouracil (5-FU) and Ibuprofen (IBU) for synergistic chemo-photothermal therapy. Demonstrating both biocompatibility and potent photothermal properties (∼32.88 %), these JNPs present a promising avenue for cancer treatment. Noteworthy is their heightened photodynamic efficiency and remarkable tumor ablation capabilities observed in vitro and in vivo, devoid of adverse effects. Furthermore, computational simulations validate their interactions with cancer cells, bolstering their utility as an emerging therapeutic modality. This endeavor pioneers a secure and efficacious strategy for cancer therapy, underscoring the significance of ß-CD-conjugated Au-Fe3O4 JNPs as innovative nanoplatforms with profound implications for the advancement of cancer therapy.

A New Language-Independent Deep CNN for Scene Text Detection and Style Transfer in Social Media Images.

Due to the adverse effect of quality caused by different social media and arbitrary languages in natural scenes, detecting text from social media images and transferring its style is challenging. This paper presents a novel end-to-end model for text detection and text style transfer in social media images. The key notion of the proposed work is to find dominant information, such as fine details in the degraded images (social media images), and then restore the structure of character information. Therefore, we first introduce a novel idea of extracting gradients from the frequency domain of the input image to reduce the adverse effect of different social media, which outputs text candidate points. The text candidates are further connected into components and used for text detection via a UNet++ like network with an EfficientNet backbone (EffiUNet++). Then, to deal with the style transfer issue, we devise a generative model, which comprises a target encoder and style parameter networks (TESP-Net) to generate the target characters by leveraging the recognition results from the first stage. Specifically, a series of residual mapping and a position attention module are devised to improve the shape and structure of generated characters. The whole model is trained end-to-end so as to optimize the performance. Experiments on our social media dataset, benchmark datasets of natural scene text detection and text style transfer show that the proposed model outperforms the existing text detection and style transfer methods in multilingual and cross-language scenario.

DFT-Based Study for the Enhancement of CO2 Adsorption on Metal-Doped Nitrogen-Enriched Polytriazines.

Nitrogen-enriched polytriazine (NPT), a carbon nitride-based material, has received much attention for CO2 storage applications. However, to enhance the CO2 uptake capacity more efficiently, it is necessary to understand the interaction mechanism between CO2 molecules and NPT through appropriate modification of the structures. Here, we introduce a method to enhance the CO2 adsorption capacity of NPT by incorporating metal atoms such as Sn, Co, and Ni into the polytriazine network. DFT calculations were used to investigate the CO2 adsorption mechanism of the polytriazine frameworks by tracking the interactions between CO2 and the various interaction sites of NPT. By optimizing the geometry of the pure and metal-containing NPT frameworks, we calculated the binding energy of metal atoms in the NPT framework, the adsorption energy of CO2 molecules, and the charge transfer between CO2 molecules and the corresponding adsorption systems. In this work, we demonstrate that the CO2 adsorption capacity of NPT can be greatly enhanced by doping transition-metal atoms into the cavities of NPT.

A Conformable Moments-Based Deep Learning System for Forged Handwriting Detection.

Detecting forged handwriting is important in a wide variety of machine learning applications, and it is challenging when the input images are degraded with noise and blur. This article presents a new model based on conformable moments (CMs) and deep ensemble neural networks (DENNs) for forged handwriting detection in noisy and blurry environments. Since CMs involve fractional calculus with the ability to model nonlinearities and geometrical moments as well as preserving spatial relationships between pixels, fine details in images are preserved. This motivates us to introduce a DENN classifier, which integrates stenographic kernels and spatial features to classify input images as normal (original, clean images), altered (handwriting changed through copy-paste and insertion operations), noisy (added noise to original image), blurred (added blur to original image), altered-noise (noise is added to the altered image), and altered-blurred (blur is added to the altered image). To evaluate our model, we use a newly introduced dataset, which comprises handwritten words altered at the character level, as well as several standard datasets, namely ACPR 2019, ICPR 2018-FDC, and the IMEI dataset. The first two of these datasets include handwriting samples that are altered at the character and word levels, and the third dataset comprises forged International Mobile Equipment Identity (IMEI) numbers. Experimental results demonstrate that the proposed method outperforms the existing methods in terms of classification rate.

MSRF-Net: A Multi-Scale Residual Fusion Network for Biomedical Image Segmentation.

Methods based on convolutional neural networks have improved the performance of biomedical image segmentation. However, most of these methods cannot efficiently segment objects of variable sizes and train on small and biased datasets, which are common for biomedical use cases. While methods exist that incorporate multi-scale fusion approaches to address the challenges arising with variable sizes, they usually use complex models that are more suitable for general semantic segmentation problems. In this paper, we propose a novel architecture called Multi-Scale Residual Fusion Network (MSRF-Net), which is specially designed for medical image segmentation. The proposed MSRF-Net is able to exchange multi-scale features of varying receptive fields using a Dual-Scale Dense Fusion (DSDF) block. Our DSDF block can exchange information rigorously across two different resolution scales, and our MSRF sub-network uses multiple DSDF blocks in sequence to perform multi-scale fusion. This allows the preservation of resolution, improved information flow and propagation of both high- and low-level features to obtain accurate segmentation maps. The proposed MSRF-Net allows to capture object variabilities and provides improved results on different biomedical datasets. Extensive experiments on MSRF-Net demonstrate that the proposed method outperforms the cutting-edge medical image segmentation methods on four publicly available datasets. We achieve the Dice Coefficient (DSC) of 0.9217, 0.9420, and 0.9224, 0.8824 on Kvasir-SEG, CVC-ClinicDB, 2018 Data Science Bowl dataset, and ISIC-2018 skin lesion segmentation challenge dataset respectively. We further conducted generalizability tests and achieved DSC of 0.7921 and 0.7575 on CVC-ClinicDB and Kvasir-SEG, respectively.

Transmission of SARS-Cov-2 and other enveloped viruses to the environment through protective gear: a brief review.

Over the past two decades, several deadly viral epidemics have emerged, which have placed humanity in danger. Previous investigations have suggested that viral diseases can spread through contaminants or contaminated surfaces. The transmission of viruses via polluted surfaces relies upon their capacity to maintain their infectivity while they are in the environment. Here, a range of materials that are widely used to manufacture personal protective equipment (PPE) are summarized, as these offer effective disinfection solutions and are the environmental variables that influence virus survival. Infection modes and prevention as well as disinfection and PPE disposal strategies are discussed. A coronavirus-like enveloped virus can live in the environment after being discharged from a host organism until it infects another healthy individual. Transmission of enveloped viruses such as SARS-CoV-2 can occur even without direct contact, although detailed knowledge of airborne routes and other indirect transmission paths is still lacking. Ground transmission of viruses is also possible via wastewater discharges. While enveloped viruses can contaminate potable water and wastewater through human excretions such as feces and droplets, careless PPE disposal can also lead to their transmission into our environment. This paper also highlights the possibility that viruses can be transmitted into the environment from PPE kits used by healthcare and emergency service personnel. A simulation-based approach was developed to understand the transport mechanism for coronavirus and similar enveloped viruses in the environment through porous media, and preliminary results from this model are presented here. Those results indicate that viruses can move through porous soil and eventually contaminate groundwater. This paper therefore underlines the importance of proper PPE disposal by healthcare workers in the Mediterranean region and around the world.

Chemical synthesis of Nd2Fe14B/Fe-Co nanocomposite with high magnetic energy product.

Nd2Fe14B is one of the most popular permanent magnets (PMs) possessing the best energy product (BH)max among the common PM materials. However, exchange-coupled nanocomposite magnets fabricated by embedding nanostructures of soft-phase magnetic materials into a hard-phase magnetic matrix manifest higher remanence and a higher energy product. Here we present the fabrication of exchange coupled Nd2Fe14B/Fe-Co magnetic nanocomposites using gel-combustion and diffusion-reduction processes. Pre-fabricated CoFe2O4 nanoparticles (NPs) of ∼5 nm diameter were incorporated into a Nd-Fe-B oxide matrix during its synthesis by gel-combustion. The obtained mixed oxide was further processed with oxidative annealing at 800 °C for 2 h and reductive annealing at 900 °C for 2 h to form a Nd2Fe14B/Fe-Co nanocomposite. Nanocomposites with different mol% of soft-phase were prepared and characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM) and physical property measurement system (PPMS) to study their crystalline phase, morphology and magnetic behavior. Addition of 7.7 mol% of soft-phase was found to be optimum, producing a coercivity (H c) of 5.6 kOe and remanence (M r) of 54 emu g-1 in the nanocomposite.

Truncated inception net: COVID-19 outbreak screening using chest X-rays.

Since December 2019, the Coronavirus Disease (COVID-19) pandemic has caused world-wide turmoil in a short period of time, and the infection, caused by SARS-CoV-2, is spreading rapidly. AI-driven tools are used to identify Coronavirus outbreaks as well as forecast their nature of spread, where imaging techniques are widely used, such as CT scans and chest X-rays (CXRs). In this paper, motivated by the fact that X-ray imaging systems are more prevalent and cheaper than CT scan systems, a deep learning-based Convolutional Neural Network (CNN) model, which we call Truncated Inception Net, is proposed to screen COVID-19 positive CXRs from other non-COVID and/or healthy cases. To validate our proposal, six different types of datasets were employed by taking the following CXRs: COVID-19 positive, Pneumonia positive, Tuberculosis positive, and healthy cases into account. The proposed model achieved an accuracy of 99.96% (AUC of 1.0) in classifying COVID-19 positive cases from combined Pneumonia and healthy cases. Similarly, it achieved an accuracy of 99.92% (AUC of 0.99) in classifying COVID-19 positive cases from combined Pneumonia, Tuberculosis, and healthy CXRs. To the best of our knowledge, as of now, the achieved results outperform the existing AI-driven tools for screening COVID-19 using the acquired CXRs, and proves the viability of using the proposed Truncated Inception Net as a screening tool.

Controlled Fabrication of Flower-Shaped Au-Cu Nanostructures Using a Deep Eutectic Solvent and Their Performance in Surface-Enhanced Raman Scattering-Based Molecular Sensing.

Controlled synthesis of anisotropic bimetallic nanostructures with tunable morphology is of great current interest for their applications in surface-enhanced Raman scattering (SERS), plasmonics, and catalysis. Despite huge effort that has been devoted so far, fabrication of bimetallic nanostructures with controlled morphology and size remained to be a great challenge, especially when their shapes are anisotropic. Here, we report a facile, one-step synthetic approach for the fabrication of anisotropic bimetallic gold-copper nanostructures (Au-Cu NSs) of the 200-300 nm size range, using choline chloride/urea (ChCl/urea)-based deep eutectic solvent (DES) as the soft template. A concentration of the CuCl2 precursor in the reaction mixture was found to impact the reduction kinetics of the metal ions, directly affecting the final morphology of the Au-Cu nanostructures and elemental distributions in them. The fabricated anisotropic Au-Cu NSs revealed a high SERS signal for crystal violet (CV) molecules adsorbed at their surfaces, with the signal enhancement factor as high as 0.21 × 106 and capacity of detecting CV molecules of concentrations as low as 10-10 M in their aqueous solutions. The growth mechanism of the anisotropic bimetallic nanostructures in DES and their SERS performance has been discussed. The simple DES-assisted synthesis strategy presented in this work can be adopted for large-scale nonaqueous fabrication of other bimetallic nanostructures in a quite "greener" way.

Re-evaluating the role of phosphinic acid (DINHOP) adsorption at the photoanode surface in the performance of dye-sensitized solar cells.

Dineohexyl phosphinic acid (DINHOP) is a popular amphiphilic molecular insulator considered as the most efficient co-adsorbent (co-grafter) for the improvement of the photovoltaic performance of TiO2 based hybrid solar cells. Although the effect of its incorporation on the improvement of cell performance has been well demonstrated, the mechanisms through which it affects the photovoltaic and electrodynamic parameters of the cells are not yet clear. Here we re-examine the mechanism through which the DINHOP co-adsorbent affects the photovoltaic and electrodynamic parameters of dye-sensitized solar cells. Although DINHOP is widely believed to inhibit (passivate) recombination across the TiO2/electrolyte interface, we demonstrate that this is sublte, noticeable only for a very high concentration (e.g. 750 µM) of DINHOP, co-sensitized with a dye. For the most frequently used DINHOP concentrations (e.g. 75 µM and 375 µM), an observed increase of the diffusion coefficient and recombination rate could be directly associated with a decrease of total intra-gap states in TiO2. For a DINHOP concentration as low as 75 µM, the conduction band edge of TiO2 moves upward due to the combined effect of charge accumulation and a decrease in the total number of intra-gap states leading to an effective enhancement of the DCCS VOC, where the decrease in total intra-gap states does not contribute positively. The decrease of total intra-gap states enhances both the transport and recombination rates of charge carriers by the same fraction due to a transport-limited recombination process. On the other hand, adsorption of DINHOP molecules at higher concentrations such as 375 µM and 750 µM additionally modifies the distribution of intra-gap states, affecting the nonlinear recombination parameter of charge carriers at the anode-electrolyte interface, leading to an overall enhancement of the DSSC VOC. In all cases, incorporation of DINHOP results in an overall improvement of the solar cell efficiency (∼14% compared with the reference one), with a maximum for a concentration of 375 µM, where no inhibition of recombination was observed. Interestingly, for this DINHOP concentration, we estimate that 1 DINHOP molecule per every 12 molecules of dye occupies the intra-gap states of the TiO2 surface. The results presented in this work elucidate the physical phenomena involved in the interaction of co-adsorbents, pre-treatments or additives with the electrolyte at the surface of the TiO2 photoanode of dye-sensitized solar cells and can be easily adapted to study other electrochemical systems.

Effect of the Electronic State of Cu, Ag, and Au on Diesel Soot Abatement: Performance of Cu/ZnO, Ag/ZnO, and Au/ZnO Catalysts.

Noble metals such as Au, Ag, and Cu supported over semiconducting ZnO are well-known heterogeneous oxidation catalysts. All of them have been utilized for the oxidation of diesel soot with varied success. However, Au-supported ZnO is seen to be superior among them. Here, we present a comparative study of all these three catalysts for diesel soot oxidation to explain why Au/ZnO is the best among them, demonstrating the contribution of electronic states of metals in composite catalysts. The electronic states of Cu, Ag, and Au determined by X-ray photoelectron spectroscopy on 1 wt % Cu/ZnO, 1 wt % Ag/ZnO, and 1 wt % Au/ZnO catalysts were correlated with their diesel soot oxidation activities. Although all three catalysts present reasonable diesel soot oxidation activities at relatively low temperature, 1% Cu/ZnO and 1% Ag/ZnO oxidize only about 60% of the deposited diesel soot around 250 °C and 1% Au/ZnO oxidizes 100% of the deposited diesel soot, at a temperature as low as 230 °C. The activity of the catalysts is attributed to the formation of stable M0-Mδ+ bifunctional catalytic sites at the metal-ZnO interface, which enhances the contact efficiency of solid diesel soot on Mδ+ and generates the superoxide species on M0 moieties. The stability of the bifunctional M0-Mδ+ sites is controlled by the electronic interactions between the metal (M) and n-type semiconductor ZnO at their interface. Very high activity of 1% Au/ZnO is attributed to the presence of Au3+ at the catalyst surface, which generates a stronger Coulombic force with diesel soot electrons. We demonstrate a direct relation between the diesel soot oxidation activity of these three metals and their electronic states at the catalyst surface.

Borohydride-Assisted Surface Activation of Co3O4/CoFe2O4 Composite and Its Catalytic Activity for 4-Nitrophenol Reduction.

Surface activation of catalysts is known to be an efficient process to enhance their activity in catalytic processes. The activation process includes the generation of oxygen vacancies, changing the nature of the catalyst surface from acidic to basic and vice versa, and the reduction of catalyst surface by H2. On the other hand, magnetically separable catalysts are highly beneficial for their utilization in water or biological fluid-based catalytic processes, as they can be easily guided to the target site and recovered. Here, we present the fabrication of CoFe2O4 and composites of Co3O4/CoFe2O4/α-Fe2O3 and Co/CoFe2O4/α-Fe2O3 through solution combustion process to utilize them as catalysts for 4-nitrophenol (4-NP) reduction. Although none of the as-prepared CoFe2O4 and Co3O4/CoFe2O4 was seen to be active in 4-NP reduction reaction, the surface of the composite gets activated by borohydride (NaBH4) treatment to act as a highly active catalyst for 4-NP reduction. X-ray photoelectron spectroscopy of the composite revealed the formation of metal-hydroxide (M-O-H) species of both Co and Fe at its surface due to borohydride treatment. The mechanism of the surface activation and the dynamics of 4-NP reduction of the surface-activated composite have been studied, proposing a possible pathway for the reduction of 4-NP.

Magnetic moment inversion at giant flux jump: dynamical property of critical state in type-II superconductors.

Experimental evidence of tremendous magnetic moment dynamical inversion, from metastable trapping state to the state with essentially the same moment oriented in the opposite direction, appearing during giant flux jump connected to thermomagnetic avalanche process in superconducting YBa2Cu3O7-δ single crystal, is presented. Magnetization inversion takes place in the system, without thermal contact between sample and sample holder, with a tremendous stored energy once the avalanche process is completed in quasi-adiabatic conditions. A model of magnetic moment inversion, caused by the jump between two metastable states of superconductor with the same energy storage, is presented and discussed in terms of the critical state with peculiar evolution of the critical-current spatial distribution. Importantly, knowledge of conditions of the appearance of such a phenomenon is crucial for applications of bulk superconductors as "permanent" magnets, for example, in superconducting levitation devices, etc.

Photocharging and Band Gap Narrowing Effects on the Performance of Plasmonic Photoelectrodes in Dye-Sensitized Solar Cells.

The incorporation of plasmonic nanostructures in active electrodes has become one of the most attractive ways to enhance the photoconversion efficiency (PCE) of dye-sensitized solar cells (DSSCs). Although an enhancement of PCE because of the incorporation of plasmonic nanostructures of different sizes, either bare or coated, has been demonstrated, the fundamental mechanisms associated to such enhancement are still unclear. Besides, the photocurrent enhancement of plasmonic DSSCs is frequently associated to the strong surface plasmon resonance (SPR) absorption of metal nanoparticles. In this work, through oxygen K-edge soft X-ray absorption and emission spectroscopies of plasmonic electrodes and electrodynamical characterization of the fabricated cells, we demonstrate a band gap narrowing and photocharging effect on the plasmonic electrodes that definitely contribute to the PCE enhancement in plasmonic DSSCs. The incorporation of bare metal nanoparticles in active metal-oxide semiconductor electrodes such as TiO2 in optimum concentration causes an upward shift of its valence band edge, reducing its effective band gap energy and enhancing the short-circuit current of DSSCs. On the other hand, small perturbation-based stepped light-induced transient measurements of photovoltage and photocurrent of the operating DSSCs revealed an upward shift of quasi-Fermi level of photoelectrodes because of the photocharging effect induced by the incorporated metal nanoparticles. The upward shift of the quasi-Fermi level causes an increase in open-circuit voltage ( VOC), nullifying the effect of band gap reduction. The short-circuit photocurrent enhancement was controlled by the band gap narrowing, screening the SPR contribution. The results presented in this work not only clarify the contribution of SPR absorption in plasmonic DSSCs, but also highlight the importance of considering the corrections in the effective base voltage because of the quasi-Fermi level band shift during the estimation of the transport and recombination parameters of an assembled DSSC.

Effects of Oxidizing/Reducing Agent Ratio on Phase Purity, Crystallinity, and Magnetic Behavior of Solution-Combustion-Grown BiFeO3 Submicroparticles.

Fabrication of phase-pure well-crystalline BiFeO3 submicroparticles in large scale is of great importance for the utilization of this rhombohedrally distorted perovskite material in applications such as memory storage and spintronic devices and visible photocatalyst for the degradation of organic pollutants. In fact, because of the narrow temperature range of phase stabilization, the fabrication of phase-pure BiFeO3 in large scale remained elusive. We present the synthesis of phase-pure BiFeO3 particles of submicrometric dimensions (246-330 nm average size) through the adjustment of oxidizing/reducing agent ratio in solution combustion process utilizing glycine as reducing agent and nitrate precursors as oxidizing agent. Utilizing X-ray diffraction and Raman spectroscopy, we demonstrate that the BiFeO3 submicroparticles synthesized at equivalence ratio (Φe) close to 0.5 do not contain undesired impurities such as Bi2Fe4O9 and Bi24Fe2O39. Moreover, the submicroparticles are highly crystalline, possessing high room temperature magnetic moment and stable antiferromagnetic behavior across a wide temperature range. The superparamagnetic behavior at low magnetic field manifested by impurities attached to the BiFeO3 submicroparticles might lead to their use as effective magnetically separable photocatalysts.

Recent progress on fabrication and drug delivery applications of nanostructured hydroxyapatite.

Through this brief review, we provide a comprehensive historical background of the development of nanostructured hydroxyapatite (nHAp), and its application potentials for controlled drug delivery, drug conjugation, and other biomedical treatments. Aspects associated with efficient utilization of hydroxyapatite (HAp) nanostructures such as their synthesis, interaction with drug molecules, and other concerns, which need to be resolved before they could be used as a potential drug carrier in body system, are discussed. This review focuses on the evolution of perceptions, practices, and accomplishments in providing improved delivery systems for drugs until date. The pioneering developments that have presaged today's fascinating state of the art drug delivery systems based on HAp and HAp-based composite nanostructures are also discussed. Special emphasis has been given to describe the application and effectiveness of modified HAp as drug carrier agent for different diseases such as bone-related disorders, carriers for antibiotics, anti-inflammatory, carcinogenic drugs, medical imaging, and protein delivery agents. As only a very few published works made comprehensive evaluation of HAp nanostructures for drug delivery applications, we try to cover the three major areas: concepts, practices and achievements, and applications, which have been consolidated and patented for their practical usage. The review covers a broad spectrum of nHAp and HAp modified inorganic drug carriers, emphasizing some of their specific aspects those needed to be considered for future drug delivery applications. This article is categorized under: Implantable Materials and Surgical Technologies > Nanomaterials and Implants Therapeutic Approaches and Drug Discovery > Nanomedicine for Respiratory Disease Nanotechnology Approaches to Biology > Cells at the Nanoscale.

Seed-Mediated Growth of Ag@Au Nanodisks with Improved Chemical Stability and Surface-Enhanced Raman Scattering.

Bimetallic Ag@Au nanoparticles (NPs) have received significant research interest because of their unique optical properties and molecular sensing ability through surface-enhanced Raman scattering (SERS). However, the synthesis of Ag@Au core-shell plasmonic nanostructures with precisely controlled size and shape remained a great challenge. Here, we report a simple approach for the synthesis of bimetallic Ag@Au nanodisks of about 13.5 nm thickness and different diameters through a seed-mediated growth process. The synthesis involves the conformal deposition of Au atoms at the corner sites of Ag nanoplate (AgNPL) seeds coupled with site-selective oxidative etching of AgNPL edges to generate Ag@Au nanodisks. The resultant Ag@Au nanodisks manifest significantly improved chemical stability and tunable localized surface plasmon resonance from the visible to the near-infrared spectral range. Moreover, in comparison to AgNPLs, the Ag@Au nanodisks showed greatly enhanced SERS performance with an enhancement factor up to 0.47 × 105, which is nearly 3-fold higher than that of the original AgNPLs (0.18 × 105). Furthermore, the Ag@Au nanodisks show a high sensitivity for detecting probe molecules such as crystal violet of concentration as low as 10-9 M and excellent reproducibility, with the SERS intensity fluctuation less than 12.5%. The synthesis route adapted for the controlled fabrication of Ag@Au nanodisks can be a potential platform for maneuvering other bimetallic plasmonic nanostructures useful for plasmonics and sensing applications.

Structural, Magnetic, and Catalytic Evaluation of Spinel Co, Ni, and Co-Ni Ferrite Nanoparticles Fabricated by Low-Temperature Solution Combustion Process.

Here, we present the low-temperature (∼600 °C) solution combustion method for the fabrication of CoFe2O4, NiFe2O4, and Co0.5Ni0.5Fe2O4 nanoparticles (NPs) of 12-64 nm range in pure cubic spinel structure, by adjusting the oxidant (nitrate ions)/reductant (glycine) ratio in the reaction mixture. Although nitrate ions/glycine (N/G) ratios of 3 and 6 were used for the synthesis, phase-pure NPs could be obtained only for the N/G ratio of 6. For the N/G ratio 3, certain amount of Ni2+ cations was reduced to metallic nickel. The NH3 gas generated during the thermal decomposition of the amino acid (glycine, H2NCH2COOH) induced the reduction reaction. X-ray diffraction (XRD), Raman spectroscopy, vibrating sample magnetometry, and X-ray photoelectron spectroscopy techniques were utilized to characterize the synthesized materials. XRD analyses of the samples indicate that the Co0.5Ni0.5Fe2O4 NPs have lattice parameter larger than that of NiFe2O4, but smaller than that of CoFe2O4 NPs. Although the saturation magnetization (M s) of Co0.5Ni0.5Fe2O4 NPs lies in between the saturation magnetization values of CoFe2O4 and NiFe2O4 NPs, high coercivity (H c, 875 Oe) of the NPs indicate their hard ferromagnetic behavior. Catalytic behavior of the fabricated spinel NPs revealed that the samples containing metallic Ni are active catalysts for the degradation of 4-nitrophenol in aqueous medium.

Static and Dynamic Synthesis of Bengali and Devanagari Signatures.

Developing an automatic signature verification system is challenging and demands a large number of training samples. This is why synthetic handwriting generation is an emerging topic in document image analysis. Some handwriting synthesizers use the motor equivalence model, the well-established hypothesis from neuroscience, which analyses how a human being accomplishes movement. Specifically, a motor equivalence model divides human actions into two steps: 1) the effector independent step at cognitive level and 2) the effector dependent step at motor level. In fact, recent work reports the successful application to Western scripts of a handwriting synthesizer, based on this theory. This paper aims to adapt this scheme for the generation of synthetic signatures in two Indic scripts, Bengali (Bangla), and Devanagari (Hindi). For this purpose, we use two different online and offline databases for both Bengali and Devanagari signatures. This paper reports an effective synthesizer for static and dynamic signatures written in Devanagari or Bengali scripts. We obtain promising results with artificially generated signatures in terms of appearance and performance when we compare the results with those for real signatures.