Abstract This article discusses the methods used to develop, evaluate, and implement new psycho-oncology interventions in clinical practice. In this regard, two world-widely used models are presented to provide scientific insight to the different actors involved in the research. Interventional research concerns clinicians, researchers, institutional actors, and patients to develop new projects using methodological rigor and to improve the conditions of patients and relatives.

Résumé
Cet article a pour objectif de décrire les méthodes pouvant être utilisées pour développer, évaluer et implé- menter en pratique clinique de nouvelles interventions en psycho-oncologie. Pour cela, deux modèles de référence à l’international… More >

E. Guerdoux, L. Coutant, M. Del Rio, S. Gourgou, F. Quenet, G. Ninot

Psycho-Oncologie, Vol.16, No.1, pp. 192-198, 2022, DOI:10.3166/pson-2022-0177

Abstract Objective: To evaluate the implementation of a daily practice using cardiac coherence in patients with peritoneal carcinosis who underwent surgery.
Materials and methods: Open, single-centre, controlled, randomized, and non-comparative phase II study, including 20 control patients versus 40 patients trained with biofeedback to use a breathing guide that will record their autonomous practice at home.
Expected results: Successful adhesion of this nonpharmacological intervention before and after surgery, which may characterize parameters in favor of its implementation and evaluation of its impact on anxiety.
Perspectives: Efficacy should then be assessed to transfer this supportive care to other patients.

Résumé
Objectif… More >

Esraa E. Shalan¹, Said S. Soliman¹, Ahmed A. Mahmoud¹, Jameel M. Al-Khayri^2,*, Salha M. ALshamrani³, Fatmah A. Safhi⁴, Areej S. Jalal⁴, Diaa Abd El-Moneim⁵, Abdallah A. Hassanin^1,*

Phyton-International Journal of Experimental Botany, Vol.92, No.7, pp. 2183-2196, 2023, DOI:10.32604/phyton.2023.028537

Abstract Determination of the somaclonal variation of in vitro-propagated plants is crucial to determine the appropriate micropropagation protocol and growth regulators for commercial scale multiplication. In this research, nine multiplication media (MM) augmented with different concentrations of 6-benzyl adenine (BA), Kinetin (Kin), and Thidiazuron (TDZ), Three rooting media (RM) supplemented with three levels of α-naphthalene acetic acid (NAA) and three types of soil mixtures (v/v); Coco peat/Vermiculite/Sand (CVS), Peat moss/Perlite/Sand (PPS) and Peat moss/Perlite (PP) were used in the micropropagation protocol of daylily plants. MM2 showed the maximum shoot length and the number of leaves, while MM9 showed the maximum number… More >

Christopher C. Rosser, Wilbur L. Walters, Abdulghani M. Abdulghani, Mokhles M. Abdulghani, Khalid H. Abed^*

Journal on Artificial Intelligence, Vol.4, No.4, pp. 261-277, 2022, DOI:10.32604/jai.2022.039703

Abstract Intrinsic motivation helps autonomous exploring agents traverse a larger portion of their environments. However, simulations of different learning environments in previous research show that after millions of timesteps of successful training, an intrinsically motivated agent may learn to act in ways unintended by the designer. This potential for unintended actions of autonomous exploring agents poses threats to the environment and humans if operated in the real world. We investigated this topic by using Unity’s Machine Learning Agent Toolkit (ML-Agents) implementation of the Proximal Policy Optimization (PPO) algorithm with the Intrinsic Curiosity Module (ICM) to train autonomous exploring agents in three… More >

WEI LIANG^1,2,*, ZONGWEI ZHANG^1,2, KEJU YANG^1,2,3, HONGTU HU^1,2, QIANG LUO^1,2, ANKANG YANG^1,2, LI CHANG⁴, YUANYUAN ZENG⁴

BIOCELL, Vol.47, No.6, pp. 1253-1263, 2023, DOI:10.32604/biocell.2023.027373

Abstract Background: Diabetic nephropathy (DN) is the most common complication of type 2 diabetes mellitus and the main cause of end-stage renal disease worldwide. Diagnostic biomarkers may allow early diagnosis and treatment of DN to reduce the prevalence and delay the development of DN. Kidney biopsy is the gold standard for diagnosing DN; however, its invasive character is its primary limitation. The machine learning approach provides a non-invasive and specific criterion for diagnosing DN, although traditional machine learning algorithms need to be improved to enhance diagnostic performance. Methods: We applied high-throughput RNA sequencing to obtain the genes related to DN tubular… More >

DER-JEU CHEN, CHENG-HUNG LAI^*

BIOCELL, Vol.47, No.6, pp. 1317-1327, 2023, DOI:10.32604/biocell.2023.028883

Abstract Background: Magnolol, a bioactive extract of the Chinese herb Magnolia officinalis has a protective effect against periodontitis. This study is aimed to explore the mechanisms involved in the functioning of magnolol against periodontitis and provide a basis for further research. Methods: Network pharmacology analysis was performed based on the identification of related targets from public databases. The Protein-protein interaction (PPI) network was constructed to visualize the significance between the targets of magnolol and periodontitis. Subsequently, Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed to predict the functions and the signal regulatory pathways involved in… More >

CHENHAO SHI¹, MAOHONG HUA², GUANHUA XU^3,*

BIOCELL, Vol.47, No.6, pp. 1329-1344, 2023, DOI:10.32604/biocell.2023.028381

Abstract Background: Ulcerative colitis (UC) is a chronic disease that often presents with abdominal pain, diarrhea, hematochezia, and significant morbidity. Gancao Xiexin decoction (GXD), a traditional Chinese medicine, has been applied for the clinical treatment of UC, while its action mechanisms are unclear. Methods: The active ingredients and their targets of GXD, and UC-related targets, were derived from public databases. Protein-protein interaction, Gene Ontology (GO), and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to analyze the important active compounds, key targets, and signaling pathways. Then, molecular docking and animal experiments were performed to verify the findings. A total… More >

Gauthier Fillières-Riveau¹ , Jean-Marie Favreau¹ , Vincent Barra¹ , Guillaume Touya²

Revue Internationale de Géomatique, Vol.30, No.1, pp. 105-126, 2020, DOI:10.3166/rig.2020.00104

Abstract Photo-realistic tactile maps are one of the tools used by visually impaired people to understand their immediate urban environment, particularly in the context of mobility, for crossing crossroads for example. These maps are nowadays mainly hand-made. In this article, we propose an approach to produce a semantic segmentation of precision aerial imagery, a central step in this manufacturing process. The different elements of interest such as sidewalks, pedestrian crossings, or central islands are thus located and traced in the urban space. We present in particular how the augmentation of this imagery by vector data from OpenStreetMap leads to significant results… More >

Salah Alzghoul^1,*, Othman Smadi¹, Ali Al Bataineh², Mamon Hatmal³, Ahmad Alamm⁴

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 455-470, 2023, DOI:10.32604/iasc.2023.038338

Abstract Currently, the decision of aortic valve replacement surgery time for asymptomatic patients with moderate-to-severe aortic stenosis (AS) is made by healthcare professionals based on the patient’s clinical biometric records. A delay in surgical aortic valve replacement (SAVR) can potentially affect patients’ quality of life. By using ML algorithms, this study aims to predict the optimal SAVR timing and determine the enhancement in moderate-to-severe AS patient survival following surgery. This study represents a novel approach that has the potential to improve decision-making and, ultimately, improve patient outcomes. We analyze data from 176 patients with moderate-to-severe aortic stenosis who had undergone or… More >

Ebu Yusuf GÜVEN, Zeynep GÜRKAŞ-AYDIN^*

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 419-437, 2023, DOI:10.32604/iasc.2023.038043

Abstract The Internet of Things (IoT) has aided in the development of new products and services. Due to the heterogeneity of IoT items and networks, traditional techniques cannot identify network risks. Rule-based solutions make it challenging to secure and manage IoT devices and services due to their diversity. While the use of artificial intelligence eliminates the need to define rules, the training and retraining processes require additional processing power. This study proposes a methodology for analyzing constrained devices in IoT environments. We examined the relationship between different sized samples from the Kitsune dataset to simulate the Mirai attack on IoT devices.… More >