The Efficacy of Deep Learning-Based Mixed Model for Speech Emotion Recognition

Human speech indirectly represents the mental state or emotion of others. The use of Artificial Intelligence (AI)-based techniques may bring revolution in this modern era by recognizing emotion from speech. In this study, we introduced a robust method for emotion recognition from human speech using a well-performed preprocessing technique together with the deep learning-based mixed model consisting of Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN). About 2800 audio files were extracted from the Toronto emotional speech set (TESS) database for this study. A high pass and Savitzky Golay Filter have been used to obtain noise-free as well as smooth audio data. A total of seven types of emotions; Angry, Disgust, Fear, Happy, Neutral, Pleasant-surprise, and Sad were used in this study. Energy, Fundamental frequency, and Mel Frequency Cepstral Coefficient (MFCC) have been used to extract the emotion features, and these features resulted in 97.5% accuracy in the mixed LSTM+CNN model. This mixed model is found to be performed better than the usual state-of-the-art models in emotion recognition from speech. It also indicates that this mixed model could be effectively utilized in advanced research dealing with sound processing

Magnetoresistance and magneto-plasmonic sensors for the detection of cancer biomarkers : A bibliometric analysis and recent advances

The conventional approaches to diagnosing cancer are expensive, often involve exposure to radiation, and struggle to identify early-stage lung cancer. As a result, the five-year survival rate is significantly reduced. Fortunately, promising alternatives using magnetoresistance (MR) and magneto-plasmonic sensors have emerged for swiftly, accurately, and inexpensively detecting cancer in its initial phases. These sensor technologies offer numerous advantages over their counterparts, such as minimal background noise, immunity to environmental influences, compatibility with nanofabrication methods, ability to detect multiple substances simultaneously, straightforward integration, high specificity, distinctive identifying capabilities, real-time monitoring, stability, label-free detection, and remarkable sensitivity for detecting individual molecules. Nevertheless, since the use of these techniques for cancer biomarker detection is relatively new, it is essential to conduct a bibliometric analysis and review recent literature to offer guidance to both early-career and established researchers in this domain. Consequently, this study performs a scientometric evaluation of the literature related to cancer biomarker detection using MR and magneto-plasmonic methods. The objective is to pinpoint current preferred techniques and challenges by examining statistics such as publication numbers, authors, countries, journals, and research interests. Furthermore, the paper also presents the latest advancements in MR and magneto-plasmonic sensors for cancer biomarker detection, with a focus on the last decade. In addition, an overview of the ongoing research in the field of MR and magneto-plasmonic sensors for detecting cancer biomarkers is highlighted. Finally, a summary on the level of current research including the significant accomplishments, challenges, and outlooks of MR and magneto-plasmonic sensors for the detection of cancer biomarkers are highlighted

Cyclodextrin nanoparticles in targeted cancer theranostics

The field of cancer nanotheranostics is rapidly evolving, with cyclodextrin (CD)-based nanoparticles emerging as a promising tool. CDs, serving as nanocarriers, have higher adaptability and demonstrate immense potential in delivering powerful anti-cancer drugs, leading to promising and specific therapeutic outcomes for combating various types of cancer. The unique characteristics of CDs, combined with innovative nanocomplex creation techniques such as encapsulation, enable the development of potential theranostic treatments. The review here focuses mainly on the different techniques administered for effective nanotheranostics applications of CD-associated complex compounds in the domain of cancer treatments. The experimentations on various loaded drugs and their complex conjugates with CDs prove effective in in vivo results. Various cancers can have potential nanotheranostics cures using CDs as nanoparticles along with a highly efficient process of nanocomplex development and a drug delivery system. In conclusion, nanotheranostics holds immense potential for targeted drug delivery and improved therapeutic outcomes, offering a promising avenue for revolutionizing cancer treatments through continuous research and innovative approaches

Carotenoids: Role in Neurodegenerative Diseases Remediation

Numerous factors can contribute to the development of neurodegenerative disorders (NDs), such as Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis, Huntington’s disease, and multiple sclerosis. Oxidative stress (OS), a fairly common ND symptom, can be caused by more reactive oxygen species being made. In addition, the pathological state of NDs, which includes a high number of protein aggregates, could make chronic inflammation worse by activating microglia. Carotenoids, often known as “CTs”, are pigments that exist naturally and play a vital role in the prevention of several brain illnesses. CTs are organic pigments with major significance in ND prevention. More than 600 CTs have been discovered in nature, and they may be found in a wide variety of creatures. Different forms of CTs are responsible for the red, yellow, and orange pigments seen in many animals and plants. Because of their unique structure, CTs exhibit a wide range of bioactive effects, such as anti-inflammatory and antioxidant effects. The preventive effects of CTs have led researchers to find a strong correlation between CT levels in the body and the avoidance and treatment of several ailments, including NDs. To further understand the connection between OS, neuroinflammation, and NDs, a literature review has been compiled. In addition, we have focused on the anti-inflammatory and antioxidant properties of CTs for the treatment and management of NDs

Dependence of the optical constant parameters of p-toluene sulfonic acid-doped polyaniline and its composites on dispersion solvents

The optical constants of Para-Toluene sulfonic acid-doped polyaniline (PANI), PANIchitosan composites, PANI-reduced graphene-oxide composites and a ternary composite comprising of PANI, chitosan and reduced graphene-oxide dispersed in diluted p-toluene sulfonic acid (PTSA) solution and N-Methyl-2-Pyrrolidone (NMP) solvent have been evaluated and compared. The optical constant values were extracted from the absorbance spectra of thin layers of the respective samples. The potential utilization of the materials as the active sensing materials of surface plasmon resonance biosensors has also been assessed in terms of the estimated value of the penetration depth through a dielectric medium. The results show a reasonable dependence of the optical constant parameters on the solvent type. Higher real part refractive index (n) and real part complex dielectric permittivity (ε’) values were observed for the samples prepared using PTSA solution, while higher optical conductivity values were observed for the NMP-based samples due to their relatively higher imaginary part refractive index (k) and imaginary part complex dielectric permittivity (ε″) values. In addition, NMP-based samples show improvement in terms of the penetration depth through a dielectric medium by around 9.5, 1.6, 4.4 and 2.9 times compared to PTSA-based samples for the PANI, PANI-chitosan, PANI-RGO and the ternary composites, respectively. Based on these, it is concluded that preparation of these materials using different dispersion solvents could produce materials of different optical properties. Thus, the variation of the dispersion solvent will allow the flexible utilization of the PANI and the composites for diverse applications

Evaluation of patients doses at medical imaging departments

Radiation exposures for medical purposes is remained the main sources to public from manmade radiation. The aims of the study are to patients’ radiation doses during specific planar radiography procedures. A total of 247 patients were examined at four radiology department in Khartoum state, Sudan. The absorbed dose to air at the center of the beam, including backscattered radiation, is known as the entrance surface air kerma (ESAK, mGy). ESAK (Ke) can be computed using the product backscatter factor (B) and incident air kerma Ki. The mean ESAK(mGy) for the chest, skull, abdomen, hip, lumbar spine and limbs procedures were 0.2, 0.76, 97, 1.88, 1.25, 2.25 and 0.30 mGy, respectively. The average ESAK (mGy) values attained for eight planar radiography procedures are comparable or slightly lesser than the previously published studies for the chest, pelvis, and limbs. The patient doses during the skull, abdomen, hip, and spinal cord (lumbar spine) are lower than the previously published values

Deformable registration of magnetic resonance images using unsupervised deep learning in neuro-/radiation oncology

Abstract Purpose Accurate deformable registration of magnetic resonance imaging (MRI) scans containing pathologies is challenging due to changes in tissue appearance. In this paper, we developed a novel automated three-dimensional (3D) convolutional U-Net based deformable image registration (ConvUNet-DIR) method using unsupervised learning to establish correspondence between baseline pre-operative and follow-up MRI scans of patients with brain glioma. Methods This study involved multi-parametric brain MRI scans (T1, T1-contrast enhanced, T2, FLAIR) acquired at pre-operative and follow-up time for 160 patients diagnosed with glioma, representing the BraTS-Reg 2022 challenge dataset. ConvUNet-DIR, a deep learning-based deformable registration workflow using 3D U-Net style architecture as a core, was developed to establish correspondence between the MRI scans. The workflow consists of three components: (1) the U-Net learns features from pairs of MRI scans and estimates a mapping between them, (2) the grid generator computes the sampling grid based on the derived transformation parameters, and (3) the spatial transformation layer generates a warped image by applying the sampling operation using interpolation. A similarity measure was used as a loss function for the network with a regularization parameter limiting the deformation. The model was trained via unsupervised learning using pairs of MRI scans on a training data set (n = 102) and validated on a validation data set (n = 26) to assess its generalizability. Its performance was evaluated on a test set (n = 32) by computing the Dice score and structural similarity index (SSIM) quantitative metrics. The model’s performance also was compared with the baseline state-of-the-art VoxelMorph (VM1 and VM2) learning-based algorithms. Results The ConvUNet-DIR model showed promising competency in performing accurate 3D deformable registration. It achieved a mean Dice score of 0.975 ± 0.003 and SSIM of 0.908 ± 0.011 on the test set (n = 32). Experimental results also demonstrated that ConvUNet-DIR outperformed the VoxelMorph algorithms concerning Dice (VM1: 0.969 ± 0.006 and VM2: 0.957 ± 0.008) and SSIM (VM1: 0.893 ± 0.012 and VM2: 0.857 ± 0.017) metrics. The time required to perform a registration for a pair of MRI scans is about 1 s on the CPU. Conclusions The developed deep learning-based model can perform an end-to-end deformable registration of a pair of 3D MRI scans for glioma patients without human intervention. The model could provide accurate, efficient, and robust deformable registration without needing pre-alignment and labeling. It outperformed the state-of-the-art VoxelMorph learning-based deformable registration algorithms and other supervised/unsupervised deep learning-based methods reported in the literature

Hall current and thermal radiation effects of 3D rotating hybrid nanofluid reactive flow via stretched plate with internal heat absorption

The present analysis deals with the impact of a magnetic field, joule heating, rotation parameter, and Hall current, as well as nonlinear thermal radiation, on a rotating hybrid Fe3O4/Al2O3 nanofluid over-stretched plate in the presence of a chemical reaction with thermophoresis and a Brownian motion parameter. The primary focus of this research is on the Brownian motion parameter. Similar transformations are used to translate the governing partial differential equations into a set of nonlinear ordinary differential equations. The shooting technique obtains numerical solutions for that system of equations. The impact of various entry parameters on transversal and longitudinal velocities, temperature, heat flow and surface shear stress are studied numerically and graphically. It was shown that there is a strong connection between the primary research when looking at particular situations that indicate how the current technique meets the convergence requirements. In addition, the physical relevance of the contributed parameters is shown via graphs and tables. The discovery demonstrates that an increase in the particle concentration of the hybrid nanofluid accelerates the flow of the fluid. In addition, factoring in dissipative heat makes it more likely that the fluid temperature will be increased to accommodate the participation of the particle concentration

An Oval-Square Shaped Split Ring Resonator Based Left-Handed Metamaterial for Satellite Communications and Radar Applications

Development of satellite and radar applications has been continuously studied to reach the demand in the recent communication technology. In this study, a new oval-square-shaped split-ring resonator with left-handed metamaterial properties was developed for C-band and X-band applications. The proposed metamaterial was fabricated on 9 × 9 × 0.508 mm3 size of Rogers RO4003C substrate. The proposed metamaterial structure was designed and simulated using Computer Simulation Technique (CST) Microwave Studio with the frequency ranging between 0 to 12 GHz. The simulated result of the proposed design indicated dual resonance frequency at 5.52 GHz (C-band) and 8.81 GHz (X-band). Meanwhile, the experimental result of the proposed design demonstrated dual resonance frequency at 5.53 GHz (C-band) and 8.31 GHz (X-band). Therefore, with a slight difference in the dual resonance frequency, the simulated result corresponded to the experimental result. Additionally, the proposed design exhibited the ideal properties of electromagnetic which is left-handed metamaterial (LHM) behavior. Hence, the metamaterial structure is highly recommended for satellite and radar applications

Measurement of Neutron Dose Equivalent within and Outside of a LINAC Treatment Vault Using a Neutron Survey Meter

This work concerns neutron doses associated with the use of a Siemens Primus M5497 electron accelerator, which is operated in the photon mode at 15 MV. The conditions offer a situation within which a fraction of the bremsstrahlung emission energies exceed the photoneutron threshold. For different field sizes, an investigation has been made of neutron dose equivalent values at various measurement locations, including: (i) At the treatment table, at a source-surface distance of 100 cm; (ii) at the level of the floor directly adjacent to the treatment table; and (iii) in the control room and patient waiting area. The evaluated neutron dose equivalent was found to range from 0.0001 to 8.6 mSv/h, notably with the greatest value at the level of the floor directly adjacent to the treatment couch (8.6 mSv/h) exceeding the greatest value on the treatment table (5.5 mSv/h). Low values ranging from unobservable to between 0.0001 to 0.0002 mSv/h neutron dose were recorded around the control room and patient waiting area. For measurements on the floor, the study showed the dose equivalent to be greatest with the jaws closed. These data, most particularly concerning neutron distribution within the treatment room, are of great importance in making steps towards improving patient safety via the provision of protective measures