Cinthia T. Lucero¹, María de los Á. Ruíz², Fabiola Pagliero¹, Carolina Castaño¹, Mariela L. Ambrosino¹, Graciela S. Lorda^1,*

Phyton-International Journal of Experimental Botany, Vol.93, No.6, pp. 1081-1099, 2024, DOI:10.32604/phyton.2024.050762

Abstract Beneficial microbes can improve soil health by promoting soil structure, nutrient cycling, and disease suppression. In addition, a wide array of rhizospheric microbes are responsible for producing metabolically active compounds including various types of plant growth regulators. So, microbial biodiversity studies could contribute to the improvement of agricultural practices in deprived areas, such as the Pampean semiarid region. The vast majority of studies conducted on endophytic microorganisms have focused on intensive crop legume species. In contrast, little attention has been paid to microorganisms of native legumes, whose ecology is not directly affected by human action.… More >

Xinkun Tang^1,2, Feng Ouyang^1,2, Ying Xu^2,*, Ligu Zhu¹, Bo Peng¹

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3955-3975, 2024, DOI:10.32604/cmc.2024.049057

Abstract High-resolution video transmission requires a substantial amount of bandwidth. In this paper, we present a novel video processing methodology that innovatively integrates region of interest (ROI) identification and super-resolution enhancement. Our method commences with the accurate detection of ROIs within video sequences, followed by the application of advanced super-resolution techniques to these areas, thereby preserving visual quality while economizing on data transmission. To validate and benchmark our approach, we have curated a new gaming dataset tailored to evaluate the effectiveness of ROI-based super-resolution in practical applications. The proposed model architecture leverages the transformer network framework,… More >

Abdullah A. Alharbi¹, Ahmad Y. Alqassim^1,*, Mohammed A. Muaddi¹, Najat H. Aldubayyan¹, Rana I. Abuhadi¹, Futon A. Akoor¹, Sarah J. Mobarki¹, Imtenan A. Oberi¹, Ghaidaa H. Alharbi¹, Yara Ajeebi¹, Adnan M. Alkhayat², Hafiz Malhan³, Mohammed Bakkar⁴, Anwar M. Makeen¹

International Journal of Mental Health Promotion, Vol.26, No.5, pp. 351-359, 2024, DOI:10.32604/ijmhp.2024.047219

Abstract Sickle Cell Anemia (SCA) is a prevalent genetic condition in Saudi Arabia, particularly in the Jazan region. The study’s purpose was to assess the prevalence of de-pression among individuals with SCA in this area and to identify the factors associated with this condition. The study involved 391 adult participants, all patients in the hematology center of Prince Mohammed bin Nasser Hospital (PMNH). Data was collected through an anonymous interview questionnaire–the Arabic version of the Patient Health Questionnaire-9 (PHQ-9)–between March–May 2022. The questionnaire covered socio-demographic information and variables related to the participant’s SCA history, such as… More >

Dandan Li^*, Changjun He^†, Junfeng Wang^†, Yanbo Wang^†, Jianlong Bu^†, Xianglong Kong^†, Dawei Sun^†

Oncology Research, Vol.26, No.3, pp. 385-400, 2018, DOI:10.3727/096504017X14973124850905

Abstract Many studies have shown that downregulation of miR-138 occurs in a variety of cancers including non-small cell lung cancer (NSCLC). However, the precise mechanisms of miR-138 in NSCLC have not been well clarified. In this study, we investigated the biological functions and molecular mechanisms of miR-138 in NSCLC cell lines, discussing whether it could turn out to be a therapeutic biomarker of NSCLC in the future. In our study, we found that miR-138 is downregulated in NSCLC tissues and cell lines. Moreover, the low level of miR-138 was associated with increased expression of SOX4 in… More >

Wang Fangzheng^*†1, Jiang Chuner^‡1, Ye Zhiming^*†, Liu Tongxin^*†, Yan Fengqin^*†, Wang Lei^*†, Li Bin^*†, Hu Fujun^*†, Chen Ming^*†, Qin Weifeng^*†, Fu Zhenfu^*†

Oncology Research, Vol.26, No.2, pp. 277-287, 2018, DOI:10.3727/096504017X15079846743590

Abstract In this retrospective review of a single institution’s experience, the efficacy and safety of the long-term use of nimotuzumab in combination with intensity-modulated radiotherapy (IMRT) and chemotherapy in the treatment of locally advanced nasopharyngeal carcinoma (NPC) were studied. Between August 2008 and March 2014, 39 newly diagnosed patients with stages III–IV NPC were treated with IMRT, chemotherapy, and nimotuzumab. Twenty patients were diagnosed with stage III (51.3%), 14 with stage IVA (35.9%), and 5 with stage IVB (12.8%) disease. All patients received at least one cycle of cisplatin-based induction chemotherapy followed by IMRT and more… More >

Hao Qi¹, Mohamed Sharaf², Andres Annuk³, Adrian Ilinca⁴, Mohamed A. Mohamed^5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1387-1404, 2024, DOI:10.32604/cmes.2024.048672

Abstract Hot dry rock (HDR) is rich in reserve, widely distributed, green, low-carbon, and has broad development potential and prospects. In this paper, a distributionally robust optimization (DRO) scheduling model for a regionally integrated energy system (RIES) considering HDR co-generation is proposed. First, the HDR-enhanced geothermal system (HDR-EGS) is introduced into the RIES. HDR-EGS realizes the thermoelectric decoupling of combined heat and power (CHP) through coordinated operation with the regional power grid and the regional heat grid, which enhances the system wind power (WP) feed-in space. Secondly, peak-hour loads are shifted using price demand response guidance More >

Abhishek Singhal^*, Devendra Kumar Sharma

Computer Systems Science and Engineering, Vol.48, No.3, pp. 609-625, 2024, DOI:10.32604/csse.2023.046730

Abstract This article presents an exhaustive comparative investigation into the accuracy of gender identification across diverse geographical regions, employing a deep learning classification algorithm for speech signal analysis. In this study, speech samples are categorized for both training and testing purposes based on their geographical origin. Category 1 comprises speech samples from speakers outside of India, whereas Category 2 comprises live-recorded speech samples from Indian speakers. Testing speech samples are likewise classified into four distinct sets, taking into consideration both geographical origin and the language spoken by the speakers. Significantly, the results indicate a noticeable difference… More >

J. Sheril Angel¹, A. Diana Andrushia^1,*, T. Mary Neebha¹, Oussama Accouche², Louai Saker², N. Anand³

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2427-2448, 2024, DOI:10.32604/cmc.2024.047326

Abstract Facial emotion recognition (FER) has become a focal point of research due to its widespread applications, ranging from human-computer interaction to affective computing. While traditional FER techniques have relied on handcrafted features and classification models trained on image or video datasets, recent strides in artificial intelligence and deep learning (DL) have ushered in more sophisticated approaches. The research aims to develop a FER system using a Faster Region Convolutional Neural Network (FRCNN) and design a specialized FRCNN architecture tailored for facial emotion recognition, leveraging its ability to capture spatial hierarchies within localized regions of facial… More >

Zohaib Ahmad Khan¹, Yuanqing Xia^1,*, Ahmed Khan², Muhammad Sadiq², Mahmood Alam³, Fuad A. Awwad⁴, Emad A. A. Ismail⁴

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2771-2793, 2024, DOI:10.32604/cmc.2024.046897

Abstract Sentiment analysis is becoming increasingly important in today’s digital age, with social media being a significant source of user-generated content. The development of sentiment lexicons that can support languages other than English is a challenging task, especially for analyzing sentiment analysis in social media reviews. Most existing sentiment analysis systems focus on English, leaving a significant research gap in other languages due to limited resources and tools. This research aims to address this gap by building a sentiment lexicon for local languages, which is then used with a machine learning algorithm for efficient sentiment analysis.… More >

Luda Chen¹, Kuangzhu Bao², Ying Chen², Jingang Hao^2,*, Jianfeng He^1,3,*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 409-427, 2024, DOI:10.32604/cmc.2024.048507

Abstract Pancreatic diseases, including mass-forming chronic pancreatitis (MFCP) and pancreatic ductal adenocarcinoma (PDAC), present with similar imaging features, leading to diagnostic complexities. Deep Learning (DL) methods have been shown to perform well on diagnostic tasks. Existing DL pancreatic lesion diagnosis studies based on Magnetic Resonance Imaging (MRI) utilize the prior information to guide models to focus on the lesion region. However, over-reliance on prior information may ignore the background information that is helpful for diagnosis. This study verifies the diagnostic significance of the background information using a clinical dataset. Consequently, the Prior Difference Guidance Network (PDGNet)… More >