Akmalbek Abdusalomov¹, Alpamis Kutlimuratov², Rashid Nasimov³, Taeg Keun Whangbo^1,*

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 2915-2933, 2023, DOI:10.32604/cmc.2023.044466

Abstract The performance of a speech emotion recognition (SER) system is heavily influenced by the efficacy of its feature extraction techniques. The study was designed to advance the field of SER by optimizing feature extraction techniques, specifically through the incorporation of high-resolution Mel-spectrograms and the expedited calculation of Mel Frequency Cepstral Coefficients (MFCC). This initiative aimed to refine the system’s accuracy by identifying and mitigating the shortcomings commonly found in current approaches. Ultimately, the primary objective was to elevate both the intricacy and effectiveness of our SER model, with a focus on augmenting its proficiency in the accurate identification of emotions… More >

LEONARDO GóMEZ ROSSO, BELéN DAVICO, EZEQUIEL LOZANO CHIAPPE, WALTER TETZLAFF, LAURA BOERO, FERNANDO BRITES, MAXIMILIANO MARTíN^*

BIOCELL, Vol.47, No.11, pp. 2361-2383, 2023, DOI:10.32604/biocell.2023.031063

Abstract Cardiovascular diseases (CVDs) are the leading cause of death globally. CVDs are a group of disorders of the heart and blood vessels and include coronary heart disease, cerebrovascular disease and rheumatic heart disease among other conditions. There are multiple independent risk factors for CVD, including hypertension, age, smoking, insulin resistance, elevated low-density lipoprotein cholesterol (LDL-C) levels, and triglyceride levels. LDL-C levels have traditionally been the target for therapies aimed at reducing CVD risk. High density lipoprotein (HDL) constitutes the only lipoprotein fraction with atheroprotective functions. Early HDL-targeted therapies have focused on increasing HDL-C levels. However, clinical trials have shown that… More > Graphic Abstract

HUI LI¹, CHENGFANG ZHOU², MEI KUANG², YUN LIU^1,*, JIEPING CHEN^1,2,*

BIOCELL, Vol.47, No.10, pp. 2177-2186, 2023, DOI:10.32604/biocell.2023.029373

Abstract Fizzy-related protein homolog 1 (FZR1) mainly functions as a specific activator of the anaphase-promoting complex/cyclosome (APC/C) in the cell cycle and controls the G0 and G1 phases of the cell cycle. We highlight recent work that has studied the role of FZR1 in tumorigenesis, growth, differentiation, and genome stability through cell-cycle control. We summarize the current state of knowledge regarding FZR1 structure, function, and the distinct ways of APC/C dysregulation in solid tumors and hematologic malignancies. We also discuss novel approaches for targeting the FZR1 as a cancer therapy and research area for future work. More >

Armin Saed-Moucheshi^1,*, Elham Rezaei Mirghaed²

Phyton-International Journal of Experimental Botany, Vol.92, No.7, pp. 1921-1941, 2023, DOI:10.32604/phyton.2023.027810

Abstract

One of the main reasons of the annual reduction in plant production all around the world is the occurrence of abiotic stresses as a result of an unpredicted changes in environmental conditions. Abiotic stresses basically trigger numerous pathways related to oxygen free radicals’ generation resulting in a higher rate of reactive oxygen species (ROS) production. Accordingly, higher rate of oxygen free radicals than its steady state causes to oxidize various types of molecules and compartments within the plants’ cells and tissues. Oxidative stress is the result of high amount free radicals of oxygen interfering with different functions leading to undergo… More >

Yun-Jung Choi¹, Youn-Joo Um^2,*

International Journal of Mental Health Promotion, Vol.25, No.3, pp. 421-431, 2023, DOI:10.32604/ijmhp.2023.023255

Abstract Major media outlets have run many articles on the COVID-19 pandemic. Since the public suffers cognitive and emotional effects related to COVID-19 from such reports, we analyzed and reviewed the topics of news reports. We searched newspaper articles with the term ‘COVID-19’ term in four Korean daily newspapers from January 20, 2020, when the first patient in Korea was found, to June 15, 2020. Topic modeling analysis was conducted through text mining using R. Five themes were found: “Changes in people’s everyday life,” “Socio-economic shock,” “Trends in infection,” “Role of the government and business,” and “Increased psychological anxiety,” which all… More >

Ali F. Khalifa¹, Eman Badr^1,2,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1995-2024, 2023, DOI:10.32604/cmc.2023.035888

Abstract Image segmentation is crucial for various research areas. Many computer vision applications depend on segmenting images to understand the scene, such as autonomous driving, surveillance systems, robotics, and medical imaging. With the recent advances in deep learning (DL) and its confounding results in image segmentation, more attention has been drawn to its use in medical image segmentation. This article introduces a survey of the state-of-the-art deep convolution neural network (CNN) models and mechanisms utilized in image segmentation. First, segmentation models are categorized based on their model architecture and primary working principle. Then, CNN categories are described, and various models are… More >

Manjur Kolhar^*, Mohammed Misfer

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 529-542, 2023, DOI:10.32604/iasc.2023.030098

Abstract Machine learning (ML) and cloud computing have now evolved to the point where they are able to be used effectively. Further improvement, however, is required when both of these technologies are combined to reap maximum benefits. A way of improving the system is by enabling healthcare workers to select appropriate machine learning algorithms for prediction and, secondly, by preserving the privacy of patient data so that it cannot be misused. The purpose of this paper is to combine these promising technologies to maintain the privacy of patient data during the disease prediction process. Treatment of heart failure may be improved… More >

Farah Mohammad^*, Saad Al-Ahmadi

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 623-639, 2023, DOI:10.32604/cmc.2023.032552

Abstract

There exists various neurological disorder based diseases like tumor, sleep disorder, headache, dementia and Epilepsy. Among these, epilepsy is the most common neurological illness in humans, comparable to stroke. Epilepsy is a severe chronic neurological illness that can be discovered through analysis of the signals generated by brain neurons and brain Magnetic resonance imaging (MRI). Neurons are intricately coupled in order to communicate and generate signals from human organs. Due to the complex nature of electroencephalogram (EEG) signals and MRI’s the epileptic seizures detection and brain related problems diagnosis becomes a challenging task. Computer based techniques and machine learning models… More >

Yu Sun, Wei Wang, Chenghai Zhao

Oncology Research, Vol.28, No.6, pp. 661-674, 2020, DOI:10.3727/096504020X16014648664459

Abstract Wnt molecules play crucial roles in development and adult homeostasis through their receptors Frizzled proteins (Fzds). Fzds mediate canonical b-catenin pathway and various noncanonical b-catenin-independent pathways. Aberrant Fzd signaling is involved in many diseases including cancer. Wnt/b-catenin is a well-established oncogenic pathway involved in almost every aspect of tumor development. However, Fzd-mediated noncanonical Wnt pathways function as both tumor promoters and tumor suppressors depending on cellular context. Fzd-targeted therapies have proven to be effective on cultured tumor cells, tumor cell xenografts, mouse tumor models, and patient-derived xenografts (PDX). Moreover, Fzd-targeted therapies synergize with chemotherapy in preclinical models. However, the occurrence… More >

John Paul¹, K. Kadirgama¹, M. Samykano^2,*, R. Saidur³, A. K. Pandey³, R. V. Mohan⁴

Energy Engineering, Vol.119, No.4, pp. 1299-1325, 2022, DOI:10.32604/ee.2022.019172

Abstract

Buildings contribute to 33% of total global energy consumption, which corresponds to 38% of greenhouse gas emissions. Enhancing building’s energy efficiency remains predominant in mitigating global warming. Advancements in thermal energy storage (TES) techniques using phase change material (PCM) have gained much attention among researchers, primarily to minimize energy consumption and to promote the use of renewable energy sources. PCM technology stays as the most promising technology for developing high-performance and energy-efficient buildings. The major drawback of PCM is its poor thermal conductivity which limits its potential use which could be resolved by dispersing conductive nanofillers. The acquired database on… More > Graphic Abstract