Exploring Emotions in EEG: Deep Learning Approach with Feature Fusion

Emotion is an intricate physiological response that plays a crucial role in how we respond and cooperate with others in our daily affairs. Numerous experiments have been evolved to recognize emotion, however still require exploration to intensify the performance. To enhance the performance of effective emotion recognition, this study proposes a subject-dependent robust end-to-end emotion recognition system based on a 1D convolutional neural network (1D-CNN). We evaluate the SJTU\footnote{\href{https://en.wikipedia.org/wiki/Shanghai_Jiao_Tong_University}{Shanghai Jiao Tong University(SJTU)}} Emotion EEG Dataset SEED-V with five emotions (happy, sad, neural, fear, and disgust). To begin with, we utilize the Fast Fourier Transform (FFT) to decompose the raw EEG signals into six frequency bands and extract the power spectrum feature from the frequency bands. After that, we combine the extracted power spectrum feature with eye movement and differential entropy (DE) features. Finally, for classification, we apply the combined data to our proposed system. Consequently, it attains 99.80\% accuracy which surpasses each prior state-of-the-art system

Identification and isolation of an agglutinin from uterus of rats

A sialic acid-binding agglutinin was purified to apparent homogeneity by affinity chromatography on fetuin-sepharose column from the rat uterine homogenate in estrus. The agglutin is Ca++ dependent, a glycoprotein, and composed of two very closely associated bands of molecular weights 28,000 and 30,000 and pIs of 4 and 4.1. Several sialoglycoproteins, sialic acid, EDTA, glucuronic acid and heparin acted as an inhibitor of the agglutinin

Multi-Objective Structural Design Optimization using Neutrosophic Goal Programming Technique

This paper develops a multi-objective Neutrosophic Goal Optimization (NSGO) technique for optimizing the design of three bar truss structure with multiple objectives subject to a specified set of constraints. In this optimum design formulation, the objective functions are weight and deflection; the design variables are the cross-sections of the bar; the constraints are the stress in member

Truss Design Optimization using Neutrosophic Optimization Technique

In this paper, we develop a neutrosophic optimization (NSO) approach for optimizing the design of plane truss structure with single objective subject to a specified set of constraints. In this optimum design formulation, the objective functions are the weight of the truss and the deflection of loaded joint; the design variables are the crosssections of the truss members; the constraints are the stresses in members. A classical truss optimization example is presented to demonstrate the efficiency of the neutrosophic optimization approach

Neutrosophic Optimization and its Application on Structural Designs

In the real world, uncertainty or vagueness is prevalent in engineering and management computations. Commonly, such uncertainties are included in the design process by introducing simplified hypothesis and safety or design factors. In case of structural and pavement design, several design methods are available to optimize objectives. But all such methods follow numerous monographs, tables and charts to find effective thickness of pavement design or optimum weight and deflection of structure calculating certain loop of algorithm in the cited iteration process. Most of the time, designers either only take help of a software or stop the cited procedure even after two or three iterations. As for example, the finite element method and genetic algorithm type of crisp optimization method had been applied on the cited topic, where the values of the input parameters were obtained from experimental data in laboratory scale. But practically, above cited standards have already ranged the magnitude of those parameters in between maximum to the minimum values. As such, the designer becomes puzzled to select those input parameters from such ranges which actually yield imprecise parameters or goals with three key governing factors i.e. degrees of acceptance, rejection and hesitancy, requiring fuzzy, intuitionistic fuzzy, and neutrosophic optimization. Therefore, the problem of structural designs, pavement designs, welded beam designs are firstly classified into single objective and multi-objective problems of structural systems. Then, a mathematical algorithm - e.g. Neutrosophic Geometric Programming, Neutrosophic Linear Programming Problem, Single Objective Neutrosophic Optimization..

Synthesis and Radiobiological Evaluation of a new 99mTc-Labeled small Peptide:99mTc-YGGSLAK as Imaging Agent

Peptides are known as receptor-specific molecules that play an important role not only in diagnosis and therapy of neoplastic diseases, but also in the pathogenesis of other diseases. In an effort to develop a peptide-based radiopharmaceutical for scintigraphic studies, a small peptide Tyr-Gly-Gly-Ser-Leu-Ala-Lys (YGGSLAK) was synthesized by Fmoc solid-phase peptide synthesis using an automated synthesizer. This peptide was analyzed by TLC, HPLC and mass spectroscopy. Then, we investigated its analytical and pharmacokinetic study after radiolabeling with technetium-99m (99mTc) using SnCl2. The radiochemical purity of the complex was over 95% and log p value was 1.46. In vivo biodistribution studies in rat showed that most activity of this injected radiolabeled peptide (99mTc-YGGSLAK) was accumulated in the liver and followed by gallbladder, intestines and kidney. Scintigraphy studies on rabbits also showed very high uptake and retention in the liver and gallbladder, and after 1 h slowly excreted through the hepatobiliary system and a little amount was also excreted through the renal system. The radiochemical and in vitro and in vivo characterization indicates that 99mTc-YGGSLAK has certain favorable properties and it might be used as a new radiopharmaceutical for hepatobiliary scintigraphy

Synthesis, Radiolabeling and Biological Evaluation of a Neutral Tripeptide and its Derivatives for Potential Nuclear Medicine Applications

Peptides are important regulators of growth and cellular functions not only in normal tissue but also in tumors. So they are becoming radioligands of increasing interest in nuclear oncology for targeted tumor diagnosis and therapy. So development of new peptide radiopharmaceuticals is becoming one of the most important areas in nuclear medicine research. A small tripeptide derivative NH2PhePheCys was synthesized by Fmoc solid phase peptide synthesis using an automated synthesizer. The oxidized form, i.e. NH2PhePheCysCysPhePheNH2, was also prepared by iodine oxidation method from NH2PhePhe- Cys(ACM). The ligands were analyzed by HPLC and mass spectroscopy. They were radiolabeled with 99mTc using SnCl2. In vitro analytical studies and biological characterizations were performed using the peptide radiopharmaceuticals. Images taken under gamma camera showed very high uptake in the liver, lung and spleen. Significant uptake was also observed in bone marrow and brain for 99mTc- NH2PhePheCys. Metabolites were produced in vivo when the radiopharmaceuticals were injected intravenously and were identified from rat brain and liver homogenate studies. Clearance through kidney did not show any evidence of breaking of the labeled compounds and formation of free 99mTc. Radiopharmaceuticals prepared using tripeptide and hexapeptide ligands were transported into the brain through blood brain barrier depending on the size and sequence characteristics. Using this property of peptide new derivatives can be prepared to develop 99mTc radiopharmaceuticals for imaging normal brain tissues as well as for diagnosing various brain disorders