Numerical Modeling of Solitons in a Low Birefringent Optical Fiber

A numerical investigation, based on the split-step Fourier transform algorithm of all optical switching of solitons in a low birefringent optical fiber is presented. The numerical algorithm is described in detail. This revised version was published online in August 2006 with corrections to the Cover Date.     

High temperature reactions of titanium(IV) oxide with some alkali persulfates and their decomposition products

The solid state reactions between TiO₂ and Na₂S₂O₈ or K₂S₂O₈ have been investigated using TG, DTG, DTA, IR, and X-ray diffraction studies in the range of 20 to 1000°C.It has been shown that TiO₂ reacts stoichiometrically (1 : 1) with Na₂S₂O₈ in the range of 160 and 220°C forming the complex sodium monoperoxodisulfato—titanium(IV) as characterized by IR and X-ray analysis. The new complex then decomposes into the reactants above 190°C.An exothermic reaction has been observed between TiO₂ and molten K₂S₂O₇ at mole ratio 1:2 respectively and higher, in the range of 280 and 350°C. The IR and X-ray analyses have shown the formation of a complex namely, potassium tetrasulfato titanium(IV) for which the formula and structure have been proposed. This complex decomposes at higher temperatures into K₂SO₄ and a mixed sulfate of potassium and titanium. The mixed sulfate melts at 620°C and decomposes into K₂SO₄, TiO₂, and the gaseous SO₃.On the other hand, Na₂S₂O₈ decomposes in a special mode producing a polymeric product of Na₁₀S₉O₃₂. Decomposition of this species occurs after melting at 560°C into Na₂SO₄ and sulfur oxides. The decomposition reaction has been proved to be catalysed by TiO₂ itself.     

Trident Nano-Indexing the Proteomics Table: Next-Version Clustering of Iron Carbide NPs and Protein Corona

Protein corona composition and precise physiological understanding of differentially expressed proteins are key for identifying disease biomarkers. In this report, we presented a distinctive quantitative proteomics table of molecular cell signaling differentially expressed proteins of corona that formed on iron carbide nanoparticles (NPs). High-performance liquid chromatography/electrospray ionization coupled with ion trap mass analyzer (HPLC/ESI-Orbitrap) and MASCOT helped quantify 142 differentially expressed proteins. Among these proteins, 104 proteins showed upregulated behavior and 38 proteins were downregulated with respect to the control, whereas 48, 32 and 24 proteins were upregulated and 8, 9 and 21 were downregulated CW (control with unmodified NPs), CY (control with modified NPs) and WY (modified and unmodified NPs), respectively. These proteins were further categorized on behalf of their regularity, locality, molecular functionality and molecular masses using gene ontology (GO). A STRING analysis was used to target the specific range of proteins involved in metabolic pathways and molecular processing in different kinds of binding functionalities, such as RNA, DNA, ATP, ADP, GTP, GDP and calcium ion bindings. Thus, this study will help develop efficient protocols for the identification of latent biomarkers in early disease detection using protein fingerprints.     

DAD-Net: Classification of Alzheimer’s Disease Using ADASYN Oversampling Technique and Optimized Neural Network

Alzheimer’s Disease (AD) is a neurological brain disorder that causes dementia and neurological dysfunction, affecting memory, behavior, and cognition. Deep Learning (DL), a kind of Artificial Intelligence (AI), has paved the way for new AD detection and automation methods. The DL model’s prediction accuracy depends on the dataset’s size. The DL models lose their accuracy when the dataset has an imbalanced class problem. This study aims to use the deep Convolutional Neural Network (CNN) to develop a reliable and efficient method for identifying Alzheimer’s disease using MRI. In this study, we offer a new CNN architecture for diagnosing Alzheimer’s disease with a modest number of parameters, making it perfect for training a smaller dataset. This proposed model correctly separates the early stages of Alzheimer’s disease and displays class activation patterns on the brain as a heat map. The proposed Detection of Alzheimer’s Disease Network (DAD-Net) is developed from scratch to correctly classify the phases of Alzheimer’s disease while reducing parameters and computation costs. The Kaggle MRI image dataset has a severe problem with class imbalance. Therefore, we used a synthetic oversampling technique to distribute the image throughout the classes and avoid the problem. Precision, recall, F1-score, Area Under the Curve (AUC), and loss are all used to compare the proposed DAD-Net against DEMENET and CNN Model. For accuracy, AUC, F1-score, precision, and recall, the DAD-Net achieved the following values for evaluation metrics: 99.22%, 99.91%, 99.19%, 99.30%, and 99.14%, respectively. The presented DAD-Net outperforms other state-of-the-art models in all evaluation metrics, according to the simulation results.     

Sub-Nominal Resolution Fourier Transform Spectrometry with Chip-Based Combs

Chip-based optical frequency combs address the demand for compact, bright, coherent light sources of equidistant phase-locked lines. Traditionally, the Fourier Transform Spectroscopy (FTS) technique is considered a suboptimal choice for resolving comb lines in chip-based sensing applications due to the requirement of long optical delays, and spectral distortion from the instrumental line shape. Here, a sub-nominal resolution FTS technique is developed that extracts the comb's offset frequency in any spectral region directly from the measured interferogram without resorting to nonlinear $$-to- $$ interferometry. This in turn enables 10's of MHz resolution spectrometry with millimeter optical retardations currently limited by the emission linewidth and phase noise of the used lasers. Low-pressure Doppler-broadened absorption lines probed by widely-tunable chip-scale mid-infrared optical frequen with electrical pumping are fully resolved over a span of tens of nanometers. This versatile technique paves the way for compact, electrostatically-actuated, or even all-on-chip high-fidelity FTS, and can be readily applied to boost the resolution of existing commercial instruments with compact interferometers several hundred times.     

Novel Bio-Based Amphiphilic Ionic Liquids for the Efficient Demulsification of Heavy Crude Oil Emulsions

In the last few decades, there has been an increasing trend for the usage of natural products and their derivatives as green and renewable oil-filed chemicals. Use of these compounds or their derivatives contributes to reducing the use of traditional chemicals, and enhances green chemistry principles. Curcumin (CRC) is one of the most popular natural products and is widely available. The green character, antioxidant action, and low cost of CRC prompt its use in several applications. In the present study, Curcumin was used to synthesize two new amphiphilic ionic liquids (AILs) by reacting with 1,3-propanesultone or bromoacetic acid to produce corresponding sulfonic and carboxylic acids, CRC-PS and CRC-BA, respectively. Following this, the formed CRC-PS and CRC-BA were allowed to react with 12-(2-hydroxyethyl)-15-(4-nonylphenoxy)-3,6,9-trioxa-12-azapentadecane-1,14-diol (HNTA) to form corresponding AILs, GCP-IL and GRB-IL, respectively. The chemical structures, surface tension, interfacial tension, and relative solubility number (RSN) of the synthesized AILs were investigated. The efficiency of GCP-IL and GRB-IL to demulsify water in heavy crude oil (W/O) emulsions was also investigated, where we observed that both GCP-IL and GRB-IL served as high-efficiency demulsifiers and the efficiency increased with a decreased ratio of water in W/O emulsion. Moreover, the data showed an increased efficiency of these AILs with an increased concentration. Among the two AILs, under testing conditions, GCP-IL exhibited a higher efficiency, shorter demulsification time, and cleaner demulsified water.     

Malformin-A1 (MA1) Sensitizes Chemoresistant Ovarian Cancer Cells to Cisplatin-Induced Apoptosis

High-grade epithelial ovarian cancer is a fatal disease in women frequently associated with drug resistance and poor outcomes. We previously demonstrated that a marine-derived compound MalforminA1 (MA1) was cytotoxic for the breast cancer cell line MCF-7. In this study, we aimed to examine the effect of MA1 on human ovarian cancer cells. The potential cytotoxicity of MA1was tested on cisplatin-sensitive (A2780S) and cisplatin-resistant (A2780CP) ovarian cancer cell lines using AlamarBlue assay, Hoechst dye, flow cytometry, Western blot, and RT-qPCR. MA1 had higher cytotoxic activity on A2780S (IC50 = 0.23 µM) and A2780CP (IC50 = 0.34 µM) cell lines when compared to cisplatin (IC50 = 31.4 µM and 76.9 µM, respectively). Flow cytometry analysis confirmed the cytotoxic effect of MA1. The synergistic effect of the two drugs was obvious, since only 13% of A2780S and 7% of A2780CP cells remained alive after 24 h of treatment with both MA1 and cisplatin. Moreover, we examined the expression of bcl2, p53, caspase3/9 genes at RNA and protein levels using RT-qPCR and Western blot, respectively, to figure out the cell death mechanism induced by MA1. A significant down-regulation in bcl2 and p53 genes was observed in treated cells compared to non-treated cells (p < 0.05), suggesting that MA1 may not follow the canonical pathway to induce apoptosis in ovarian cancer cell lines. MalforminA1 showed promising anticancer activity by inducing cytotoxicity in cisplatin-sensitive and cisplatin-resistant cancer cell lines. Interestingly, a synergistic effect was observed when MA1 was combined with cisplatin, leading to it overcoming its resistance to cisplatin.     

A Robust 3D Cage‐like Ultramicroporous Network Structure with High Gas‐Uptake Capacity

A three‐dimensional (3D) cage‐like organic network (3D‐CON) structure synthesized by the straightforward condensation of building blocks designed with gas adsorption properties is presented. The 3D‐CON can be prepared using an easy but powerful route, which is essential for commercial scale‐up. The resulting fused aromatic 3D‐CON exhibited a high Brunauer–Emmett–Teller (BET) specific surface area of up to 2247 m² g^?1. More importantly, the 3D‐CON displayed outstanding low pressure hydrogen (H₂, 2.64 wt %, 1.0 bar and 77 K), methane (CH₄, 2.4 wt %, 1.0 bar and 273 K), and carbon dioxide (CO₂, 26.7 wt %, 1.0 bar and 273 K) uptake with a high isosteric heat of adsorption (H₂, 8.10 kJ mol^?1; CH₄, 18.72 kJ mol^?1; CO₂, 31.87 kJ mol^?1). These values are among the best reported for organic networks with high thermal stability (ca. 600 °C).