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  • Open Access

    ARTICLE

    Experience of Mental Health Professionals Collaborating with Peer Supporters in a Community Mental Health Service Team

    Sowon Lee1, Boyoung Kim1,*, Chung Kil Park2,*

    International Journal of Mental Health Promotion, Vol.26, No.4, pp. 251-260, 2024, DOI:10.32604/ijmhp.2024.048803

    Abstract This study explored how mental health professionals collaborate with peer supporters with mental disabilities in a community mental health institution. From January 19 to February 23, 2021, three 60 min interviews were conducted with six mental health professionals working at a Korean community center. The results were qualitatively analyzed and divided into four themes and eight categories. The four themes were the perceptions of and challenges in working with peer supporters with mental disabilities, conflict and confusion about working with peer supporters, forming partnerships with peer supporters, and policy support for peer supporters’ job security. Participants reported vague anxiety about… More >

  • Open Access

    ARTICLE

    Various Organic Nutrient Sources in Combinations with Inorganic Fertilizers Influence the Yield and Quality of Sweet Corn (Zea mays L. saccharata) in New Alluvial Soils of West Bengal, India

    Anindita Das1, Kanu Murmu2, Biplab Mitra3, Pintoo Bandopadhyay2, Ritesh Kundu4, Moupiya Roy5, Saleh Alfarraj6, Mohammad Javed Ansari7, Marian Brestic8, Akbar Hossain9,*

    Phyton-International Journal of Experimental Botany, Vol.93, No.4, pp. 763-776, 2024, DOI:10.32604/phyton.2024.049473

    Abstract Nutrient management plays a crucial role in the yield and quality of sweet corn. A field experiment was conducted in consecutive two kharif seasons in 2018 and 2019 to investigate the effect of various organic sources of nutrients in combination with inorganic sources on the yield and quality of sweet corn under new alluvial soils of West Bengal, India. Treatments were: T: Control (without fertilizers); T: 100% recommended dose (RDF) of chemical fertilizers (CF) (RDF CF); T: 100% recommended dose of N (RDN) through vermicompost (VC) (RDN VC); T: 50 RDN through CF + 50% RDN through VC (RDN CF… More >

  • Open Access

    ARTICLE

    Stigma-Specific Comparative Proteomic Analysis Reveals the Distyly Response to Self-Incompatibility in Plumbago auriculata Lam

    Di Hu1, Shouli Yi1,*, Di Lin2, Suping Gao3, Ting Lei3, Wenji Li4, Tingdan Xu1, Songlin Jiang1

    Phyton-International Journal of Experimental Botany, Vol.93, No.4, pp. 681-697, 2024, DOI:10.32604/phyton.2024.049166

    Abstract In plants, heteromorphic self-incompatibility (HetSI) is a strategy for avoiding self-pollination and promoting outcrossing, and during this process, numerous protein-protein interaction events occur between the pistil and pollen. Previous studies in Primula and Fagopyrum that focused on HetSI systems have provided interesting insights; however, the molecular mechanism underlying HetSI remains largely unknown. In this study, we profiled the proteome of Plumbago auriculata stigmas before and after self-incompatible (SI) and self-compatible (SC) pollination. Comparative analyses were conducted by 4D-DIA (Four-dimensional data independent acquisition), a promising technology that increases the sensitivity and reduces the spectral complexity of proteomic analysis by adding a… More >

  • Open Access

    ARTICLE

    Profiles of the Headspace Volatile Organic and Essential Oil Compounds from the Tunisian Cardaria draba (L.) Desv. and Its Leaf and Stem Epidermal Micromorphology

    Wissal Saadellaoui1, Samiha Kahlaoui1, Kheiria Hcini1, Abir Haddada1, Noomene Sleimi2,*, Roberta Ascrizzi3, Guido Flamini3, Fethia Harzallah-Skhiri4, Sondes Stambouli-Essassi1

    Phyton-International Journal of Experimental Botany, Vol.93, No.4, pp. 725-744, 2024, DOI:10.32604/phyton.2024.048110

    Abstract In this work, we investigated aroma volatiles emanated by dry roots, stems, leaves, flowers, and fruits of Cardaria draba (L.) Desv. growing wild in Tunisia and its aerial part essential oils (EOs) composition. A total of 37 volatile organic compounds (96.7%–98.9%) were identified; 4 esters, 4 alcohols, 7 hydrocarbons, 12 aldehydes, 5 ketones, 1 lactone, 1 organosulfur compound, 2 organonitrogen compounds, and 1 acid. The hydrocarbons form the main group, representing 49.5%–84.6% of the total detected volatiles. The main constituent was 2,2,4,6,6-pentamethylheptane (44.5%–76.2%) reaching the highest relative percentages. Forty-two compounds were determined in the two fractions of EOs, representing 98.8%… More >

  • Open Access

    ARTICLE

    Big Data Access Control Mechanism Based on Two-Layer Permission Decision Structure

    Aodi Liu, Na Wang*, Xuehui Du, Dibin Shan, Xiangyu Wu, Wenjuan Wang

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1705-1726, 2024, DOI:10.32604/cmc.2024.049011

    Abstract Big data resources are characterized by large scale, wide sources, and strong dynamics. Existing access control mechanisms based on manual policy formulation by security experts suffer from drawbacks such as low policy management efficiency and difficulty in accurately describing the access control policy. To overcome these problems, this paper proposes a big data access control mechanism based on a two-layer permission decision structure. This mechanism extends the attribute-based access control (ABAC) model. Business attributes are introduced in the ABAC model as business constraints between entities. The proposed mechanism implements a two-layer permission decision structure composed of the inherent attributes of… More >

  • Open Access

    ARTICLE

    KurdSet: A Kurdish Handwritten Characters Recognition Dataset Using Convolutional Neural Network

    Sardar Hasen Ali*, Maiwan Bahjat Abdulrazzaq

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 429-448, 2024, DOI:10.32604/cmc.2024.048356

    Abstract Handwritten character recognition (HCR) involves identifying characters in images, documents, and various sources such as forms surveys, questionnaires, and signatures, and transforming them into a machine-readable format for subsequent processing. Successfully recognizing complex and intricately shaped handwritten characters remains a significant obstacle. The use of convolutional neural network (CNN) in recent developments has notably advanced HCR, leveraging the ability to extract discriminative features from extensive sets of raw data. Because of the absence of pre-existing datasets in the Kurdish language, we created a Kurdish handwritten dataset called (KurdSet). The dataset consists of Kurdish characters, digits, texts, and symbols. The dataset… More >

  • Open Access

    ARTICLE

    Leveraging User-Generated Comments and Fused BiLSTM Models to Detect and Predict Issues with Mobile Apps

    Wael M. S. Yafooz*, Abdullah Alsaeedi

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 735-759, 2024, DOI:10.32604/cmc.2024.048270

    Abstract In the last decade, technical advancements and faster Internet speeds have also led to an increasing number of mobile devices and users. Thus, all contributors to society, whether young or old members, can use these mobile apps. The use of these apps eases our daily lives, and all customers who need any type of service can access it easily, comfortably, and efficiently through mobile apps. Particularly, Saudi Arabia greatly depends on digital services to assist people and visitors. Such mobile devices are used in organizing daily work schedules and services, particularly during two large occasions, Umrah and Hajj. However, pilgrims… More >

  • Open Access

    ARTICLE

    Combined CNN-LSTM Deep Learning Algorithms for Recognizing Human Physical Activities in Large and Distributed Manners: A Recommendation System

    Ameni Ellouze1, Nesrine Kadri2, Alaa Alaerjan3,*, Mohamed Ksantini1

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 351-372, 2024, DOI:10.32604/cmc.2024.048061

    Abstract Recognizing human activity (HAR) from data in a smartphone sensor plays an important role in the field of health to prevent chronic diseases. Daily and weekly physical activities are recorded on the smartphone and tell the user whether he is moving well or not. Typically, smartphones and their associated sensing devices operate in distributed and unstable environments. Therefore, collecting their data and extracting useful information is a significant challenge. In this context, the aim of this paper is twofold: The first is to analyze human behavior based on the recognition of physical activities. Using the results of physical activity detection… More >

  • Open Access

    ARTICLE

    Sepsis Prediction Using CNNBDLSTM and Temporal Derivatives Feature Extraction in the IoT Medical Environment

    Sapiah Sakri1, Shakila Basheer1, Zuhaira Muhammad Zain1, Nurul Halimatul Asmak Ismail2,*, Dua’ Abdellatef Nassar1, Manal Abdullah Alohali1, Mais Ayman Alharaki1

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1157-1185, 2024, DOI:10.32604/cmc.2024.048051

    Abstract Background: Sepsis, a potentially fatal inflammatory disease triggered by infection, carries significant health implications worldwide. Timely detection is crucial as sepsis can rapidly escalate if left undetected. Recent advancements in deep learning (DL) offer powerful tools to address this challenge. Aim: Thus, this study proposed a hybrid CNNBDLSTM, a combination of a convolutional neural network (CNN) with a bi-directional long short-term memory (BDLSTM) model to predict sepsis onset. Implementing the proposed model provides a robust framework that capitalizes on the complementary strengths of both architectures, resulting in more accurate and timelier predictions. Method: The sepsis prediction method proposed here utilizes… More >

  • Open Access

    REVIEW

    Internet of Things Authentication Protocols: Comparative Study

    Souhayla Dargaoui1, Mourade Azrour1,*, Ahmad El Allaoui1, Azidine Guezzaz2, Abdulatif Alabdulatif3, Abdullah Alnajim4

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 65-91, 2024, DOI:10.32604/cmc.2024.047625

    Abstract Nowadays, devices are connected across all areas, from intelligent buildings and smart cities to Industry 4.0 and smart healthcare. With the exponential growth of Internet of Things usage in our world, IoT security is still the biggest challenge for its deployment. The main goal of IoT security is to ensure the accessibility of services provided by an IoT environment, protect privacy, and confidentiality, and guarantee the safety of IoT users, infrastructures, data, and devices. Authentication, as the first line of defense against security threats, becomes the priority of everyone. It can either grant or deny users access to resources according… More >

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