Narcissistic self-sorting in Zn(II) porphyrin derived semiconducting nanostructures

The narcissistic self-sorted phenomenon is explicitly attributed to the structural similarities in organic molecules. Although such relevant materials are rarely explored, self-sorted structures from macrocyclic π-conjugated-based p- and n-type organic semiconductors facilitate the increase of exciton dissociation and charge separation in bulk heterojunction solar cells. Herein, we report two extended π-conjugated derivatives consisting of zinc-porphyrin-linked benzothiadiazole acting as an acceptor (PB) and anthracene as a donor (PA). Despite having the same porphyrin π-conjugated core in PA and PB, variations in donor and acceptor moieties make the molecular packing form one-dimensional (1D) self-assembled nanofibers via H- and J-type aggregates. Interestingly, a dissimilar aggregate of PA and PB exists as a mixture (PA + PB), promoting narcissistic self-sorted structures. Electrochemical impedance investigation reveals that the electronic characteristics of self-sorting assemblies are influenced by the difference in electrostatic potentials for PA and PB, resulting in a transitional electrical conductivity of 0.14 S cm-1. Therefore, the design of such materials for the fabrication of effective photovoltaics is promoted by these extraordinary self-sorted behaviors in comparable organic π-conjugated molecules.

Non-invasive glucose prediction and classification using NIR technology with machine learning

In this paper, a dual wavelength short near-infrared system is described for the detection of glucose levels. The system aims to improve the accuracy of blood glucose detection in a cost-effective and non-invasive way. The accuracy of the method is evaluated using real-time samples collected with the reference finger prick glucose device. A feed forward neural network (FFNN) regression method is employed to predict glucose levels based on the input data obtained from NIR technology. The system calculates glucose evaluation metrics and performs Surveillance error grid (SEG) analysis. The coefficient of determination R 2 and mean absolute error are observed 0.99 and 2.49 mg/dl, respectively. Additionally, the system determines the root mean square error (RMSE) as 3.02 mg/dl. It also shows that the mean absolute percentage error (MAPE) is 1.94% and mean squared error (MSE) is 9.16 ( m g / d l ) 2 for FFNN. The SEG analysis shows that the glucose values measured by the system fall within the clinically acceptable range when compared to the reference method. Finally, the system uses the multi-class classification method of the multilayer perceptron (MLP) and K-nearest neighbors (KNN) classifier to classify glucose levels with an accuracy of 99%.

Effect of temperature and pH on the structure and stability of tumor-specific lectin jacalin and insights into the location of its tryptophan residues: CD, DSC and fluorescence studies

Jacalin, the jackfruit seed lectin, exhibits high specificity for the tumor-specific T-antigen and is used in various biomedical and biotechnological applications. Here, we report biophysical studies on the thermal unfolding of jacalin and the effect of pH and temperature on its secondary structure. Differential scanning calorimetric (DSC) studies revealed that native jacalin unfolds at ∼60 °C and that carbohydrate binding stabilizes the protein structure. Circular dichroism spectroscopic studies indicated that the secondary structure of jacalin remains mostly unaffected over pH 2.0-9.0, whereas considerable changes were observed in the tertiary structure. DSC experiments demonstrated that jacalin exhibits two overlapping transitions between pH 2 and 5, which could be attributed to dissociation of the tetrameric protein into subunits and their unfolding. Interestingly, only one transition between pH 6 and 9 was observed, suggesting that the subunit dissociation and unfolding occur simultaneously. While quenching of the protein intrinsic fluorescence by acrylamide increased significantly upon carbohydrate binding, quenching by succinimide is essentially unaffected. We attribute this difference to increased exposure of Trp-123 in the α-chain as it is involved in carbohydrate binding. Both acrylamide and succinimide gave biphasic Stern-Volmer plots, consistent with differential accessibility of the two tryptophan residues of jacalin to them.

EEG-BCI-based motor imagery classification using double attention convolutional network

This article aims to improve and diversify signal processing techniques to execute a brain-computer interface (BCI) based on neurological phenomena observed when performing motor tasks using motor imagery (MI). The noise present in the original data, such as intermodulation noise, crosstalk, and other unwanted noise, is removed by Modify Least Mean Square (M-LMS) in the pre-processing stage. Traditional LMSs were unable to extract all the noise from the images. After pre-processing, the required features, such as statistical features, entropy features, etc., were extracted using Common Spatial Pattern (CSP) and Pearson's Correlation Coefficient (PCC) instead of the traditional single feature extraction model. The arithmetic optimization algorithm cannot select the features accurately and fails to reduce the feature dimensionality of the data. Thus, an Extended Arithmetic operation optimization (ExAo) algorithm is used to select the most significant attributes from the extracted features. The proposed model uses Double Attention Convolutional Neural Networks (DAttnConvNet) to classify the types of EEG signals based on optimal feature selection. Here, the attention mechanism is used to select and optimize the features to improve the classification accuracy and efficiency of the model. In EEG motor imagery datasets, the proposed model has been analyzed under class, which obtained an accuracy of 99.98% in class Baseline (B), 99.82% in class Imagined movement of a right fist (R) and 99.61% in class Imagined movement of both fists (RL). In the EEG dataset, the proposed model can obtain a high accuracy of 97.94% compared to EEG datasets of other models.

Conducting 1D nanostructures from light-stimulated copper-metalated porphyrin-dibenzothiophene

Control over the dimensionality of stimulated organic semiconductors has aroused significant interest in organic electronics; however, the design of such materials still remains to be decided. Herein, we have developed three dibenzothiophene-appended freebase, zinc-metalated and copper-metalated porphyrin derivatives (PFb-DBT, PZn-DBT and PCu-DBT) in which PCu-DBT leads to an anion-binding complex in chloroform upon the application of light, resulting in self-assembled 1D nanostructures with high electrical conductivity. Nevertheless, light-stimulated freebase and zinc-metalated P-DBT undergo protonation and demetalation. Electron microscopic images displayed the anion-binding-assisted 1D nanostructure using weak non-covalent interactions, which promotes enhancement in electrical conductivity among other things, as confirmed by electrochemical impedance spectra. Thus, the generation of well-defined nanostructures with improved electronic characteristics from stimuli-responsive organic dyes suggests the importance of developing various smart materials for efficient field effect transistors and sensors.

Photo-induced intramolecular electron transfer in phenoxazine-phthalocyanine donor-acceptor systems

Donor-Acceptor (D-A) systems based on phenoxazine – phthalocyanine (PXZ-Pc) and phenoxazine – zinc phthalocyanine (PXZ-ZnPc) have been designed and synthesized. Both D-A systems are characterized using various spectroscopic and electrochemical techniques including in-situ methods. Optical absorption studies suggest that both Soret and Q bands of these D-A systems are hypsochromically and bathochromically shifted, when compared to its individual constituents. The study supported by theoretical calculations shows clearly that there exists a negligible electronic communication in the ground state between donor phenoxazine and acceptor phthalocyanine. However, attractively, both D-A systems exhibit noteworthy fluorescence emission quenching (90–99%) of the phthalocyanine emission compared to its reference compounds. The fluorescence emission quenching featured at the excited-state intramolecular photoinduced electron transfer from ground state of phenoxazine to the excited state of phthalocyaine/zinc phthalocyanine. The rates of electron-transfer ([Formula: see text] of these D-A systems are found in the range of 5.7 × 108 to 2.8 × 109 s[Formula: see text] and are according to solvent polarity.

Modelling and Analysis of Microcontroller Based MPPT Method Using FPGA

Now days, the renewable energy sources (RES) are the most accomplished system for power generation. In this paper, focus on FPGA based digital controller for the grid connected DG system. The study and performance analysis of grid-connected PV system as follows to improve the efficiency of the grid system and to extract the maximum power. This work is designed & development of FPGA. The DC power and battery capture on the DC bus system we have maintained the unity power factor and harmonics current in the DG system. The bi-directional battery systems also provide quick response & the performance under the variable DC voltage. Then, to develop the effectiveness control strategy is to manage the power flow equally AC & DC sides. This system simulated in MTTLAB Tools and FPGA System.

Porphyrin-based supramolecular assemblies and their applications in NLO and PDT

Tetrapyrrolic systems largely inspired by nature have attracted much attention in organic electronics and biomedical applications owing to their planar structure and extended [Formula: see text]-conjugated double bonds. As a result, delocalization of [Formula: see text]-electron cloud leads the excellent optical absorption and fluorescent properties. Nonetheless, the utilization of non-covalent interactions result in the self-assembled nanostructures providing applications in bioimaging and electronics. In this review, it is demonstrated that the recent reports on the self-assembly in tetrapyrrolic systems via supramolecular interactions lead to well-defined nanoarchitectures. Moreover, the importance of porphyrin based derivatives in nanoelectronics and chemotherapeutic applications is reported. Therefore, the inclination of tetrapyrroles towards the design and development of novel supramolecular nanostructures are considered the hallmark for nanorobotics, shape memory polymers and bionic arms.

Physicochemical properties of cookies enriched with xylooligosaccharides

The growing commercial importance of xylooligosaccharides is based on their beneficial health properties, particularly their ability to stimulate the growth and activity of intestinal bacteria such as Bifidobacterium and Lactobacillus species. Xylooligosaccharides are less sweet, acid, and heat stable, with low recommended levels of intake compared to other oligosaccharides. In view of the consumer demand for foods with low sugar, low fat, and high fiber contents, they are suitable for incorporation into bakery products. In this study, we have developed wheat-based cookies incorporated with xylooligosaccharides at 5%, 10%, and 15% levels. The nutritive value and physicochemical properties of the cookies changed with xylooligosaccharides incorporation; both crude fiber and dietary fiber contents increased by 14% and 35%, respectively, in the enriched cookies. The moisture levels increased with increase in the percentage of xylooligosaccharides incorporated. Cookies with 5% xylooligosaccharides were found most acceptable, although the color was slightly darker compared to the control, while cookies with 10% and 15% xylooligosaccharides were softer and darker and therefore less acceptable. Enrichment with xylooligosaccharides at 5% provided a product stable for 21 days at room temperature (25 ± 2℃). The storage stability of cookies with higher levels of xylooligosaccharides was less than the 5% xylooligosaccharides cookies and control. The retention of the prebiotic xylooligosaccharides in the products was relatively high (74%).