Article
Multidisciplinary Sciences
Ke Mo, Yu Zhang, Zheng Dong, Yuhang Yang, Xiaoqiang Ma, Ben L. Feringa, Depeng Zhao
Summary: Scientists have designed synthetic molecular motors that can be driven by chemical energy and have intrinsic control over the direction of rotation, simple autonomous motion, and near-perfect unidirectionality. This study demonstrates the potential for future generations of multicomponent machines to perform mechanical functions.
Article
Biochemistry & Molecular Biology
Alana N. Vagnozzi, Jian-Guo Li, Jin Chiu, Roshanak Razmpour, Rebecca Warfield, Servio H. Ramirez, Domenico Pratico
Summary: VPS35 plays a crucial role in tau metabolism and neuropathology, with its overexpression reducing pathological tau in neuronal cells while genetic silencing leads to accumulation. The availability of active cathepsin D mediates the effect of VPS35 on pathological tau accumulation, making it a potential therapeutic target for human tauopathies.
MOLECULAR PSYCHIATRY
(2021)
Article
Behavioral Sciences
Etedal Ahmed A. Ibrahim, Ghada A. Mutaal Badri, Khabab Abbasher Hussien Mohamed Ahmed, Mohammed Eltahier Abdalla Omer
Summary: The study found that environmental conditions were the most common triggers of migraine headache among Sudanese patients, while Acetaminophen was the most commonly used drug for relieving migraine in this population. The majority of patients were female (80%), aged 26-35 years (56.9%), and a significant proportion were housewives (40%).
BRAIN AND BEHAVIOR
(2021)
Review
Humanities, Multidisciplinary
Ahmad Fekry Moussa, Ibrahim Suleiman Al Qatawneh, Moustafa Elmetwaly Kandeel
Summary: This study focuses on the procedural necessity of primary investigations in the Arab countries, particularly in Egypt. It analyzes the position of the Arab procedural legislation and judiciary systems regarding procedural necessity and argues against expanding discretionary powers that may lead to abuse of officials and restrict individual rights and freedoms.
HUMANITIES & SOCIAL SCIENCES COMMUNICATIONS
(2022)
Article
Physics, Multidisciplinary
Gabriel Koch Ocker
Summary: This study presents a statistical field theory for networks of integrate-and-fire neurons with stochastic spike emission, revealing the impact of spike-driven reset of the membrane voltage on population activity. The study uncovers bistability and fluctuation effects in the mean-field dynamics, as well as the roles of spike resets and recurrent inhibition in stabilizing network activity. It also calculates the phase diagram for inhibitory stabilization and finds that wide regions of parameter space exhibit inhibition-stabilized regime.
Article
Education & Educational Research
Olga Garanina, Nidal Al Said, Valery Stepenko, Marija Troyanskaya
Summary: The study developed and tested an original model illustrating personality development in the information society, finding that its implementation increased students' use of resources for personal growth. The model's practical value lies in its applicability to higher education systems in various countries, especially in the context of distance learning and social isolation caused by the COVID-19 pandemic.
EDUCATION AND INFORMATION TECHNOLOGIES
(2021)
Article
Agricultural Engineering
Jiangkuan Xing, Ryoichi Kurose, Kun Luo, Jianren Fan
Summary: Researchers have developed a new tool for establishing solid fuel conversion kinetics from thermogravimetric analysis (TGA) measurements using chemistry-informed machine learning approaches. The derived pyrolysis kinetics accurately reproduce the pyrolysis process for different biomass types and demonstrate advantages in predicting volatiles yield.
BIORESOURCE TECHNOLOGY
(2022)
Article
Biology
Christine E. Sosiak, Marek L. Borowiec, Phillip Barden
Summary: Among the social insects, army ants are unique with their coordinated predation, nomadic lifestyle, and specialized wingless queens. This study reports the discovery of the oldest army ant fossil from the Eocene period, named Dissimulodorylus perseus, and reveals unexpected diversity of now-extinct army ant lineages in the Cenozoic.
Article
Mathematics
Chang Wan, Fei Deng, Shitao Li, S. Omidbakhsh Amiri, A. A. Talebi, H. Rashmanlou
Summary: This paper introduces the method of using bipolar fuzzy graph algorithms to solve practical problems, and classifies bipolar fuzzy graphs by the concept of (θ, δ)-homomorphisms. The paper also presents an application of homomorphism of bipolar fuzzy graphs.
JOURNAL OF MATHEMATICS
(2022)
Article
Engineering, Biomedical
Ruslan Garifullin, Mustafa O. Guler
Summary: This review discusses the use of self-assembling peptide molecules and electroactive units in supramolecular functional electronic and optical materials, with potential biomedical and bioelectronics applications.
MATERIALS TODAY BIO
(2021)
Review
Plant Sciences
Muhammad Amir Qureshi, Aamir Lal, Muhammad Shah Nawaz-ul-Rehman, Thuy Thi Bich Vo, Gusti Ngurah Prabu Wira Sanjaya, Phuong Thi Ho, Bupi Nattanong, Eui-Joon Kil, Shah Mohammad Hemayet Jahan, Kyeong-Yeoll Lee, Chi-Wei Tsai, Hang Thi Dao, Trinh Xuan Hoat, Tin-Tin Aye, Nang Kyu Win, Jangha Lee, Sang-Mok Kim, Sukchan Lee
Summary: Plant viruses are responsible for devastating plant diseases worldwide, particularly in tropical and subtropical regions. The emergence of new begomoviruses, a genus of plant viruses transmitted by insects, has become a major concern due to their increasing host range and geographical expansion. Four highly destructive begomoviruses from Asia have been identified, causing massive economic losses in Europe. Understanding the characteristics of these emerging viruses is crucial for implementing preventive measures.
FRONTIERS IN PLANT SCIENCE
(2022)
Article
Humanities, Multidisciplinary
Ulbossyn Tuyakova, Bibianar Baizhumanova, Talshyn Mustapaeva, Lyazzat Alekeshova, Zhansaya Otarbaeva
Summary: This study investigates the impact of teaching emotional intelligence on the emotional competence of social pedagogue students. The results show significant improvement in various aspects of emotional intelligence, highlighting the value of further research in this area and the benefits of enhancing teacher's emotional intelligence for teaching and learning.
HUMANITIES & SOCIAL SCIENCES COMMUNICATIONS
(2022)
Article
Thermodynamics
Shuo Wang
Summary: The study conducted through numerical simulation found that square and cylindrical furnaces have more complete combustion, lower heat loss, but higher NOx emissions; cylindrical furnaces with smaller dip angles have reduced internal reflux, lower reaction rates, higher heat absorption, and lower NOx concentrations at the outlet.
APPLIED THERMAL ENGINEERING
(2022)
Review
Biochemistry & Molecular Biology
Traian Constantin, Mihai Pavalean, Stefana Bucur, Maria Magdalena Constantin, Alin Codrut Nicolescu, Irina Pacu, Victor Madan
Summary: Bladder cancer animal models can be categorized as either autochthonous or non-autochthonous, with the non-autochthonous models further classified into syngeneic and xenograft models. These models have different characteristics and applications based on the type of tumor implantation.
Article
Pharmacology & Pharmacy
Bin Chen, Linguangjin Wu, Xiaoxia Tang, Ting Wang, Shuyun Wang, Hongjie Yu, Guangsheng Wan, Manli Xie, Ruijuan Zhang, Haijuan Xiao, Wanli Deng
Summary: Quercetin inhibits the tumorigenesis of CRC by inhibiting the polarization of M2 macrophages and downregulating hsa_circ_0006990. This finding provides useful insights for exploring new methods of treating CRC.
FRONTIERS IN PHARMACOLOGY
(2022)
Article
Polymer Science
Zaid Alhulaybi, Ibrahim Dubdub, Mohammed Al-Yaari, Abdulrahman Almithn, Abdullah F. Al-Naim, Haidar Aljanubi
Summary: This study aims to build knowledge on the kinetics of PLA pyrolysis using TGA and four model-free methods (Friedman, FWO, KAS, and Starink), for application in the textile and food packaging fields. The obtained activation energies of PLA pyrolysis by the model-free methods were in good agreement, ranging from 97 to 109 kJ/mol. The best controlling reaction mechanism of PLA pyrolysis was identified as the geometrical contraction model (R2) through the Criado and Coats-Redfern models.
Article
Mathematics
Mohammed Abdullah Ammer, Zeyad A. T. Ahmed, Saleh Nagi Alsubari, Theyazn H. H. Aldhyani, Shahab Ahmad Almaaytah
Summary: Artificial intelligence assists in selecting the right candidates for specific jobs and helps organizations make accurate hiring decisions, while identifying strengths and weaknesses. This study contributes to the application of AI in human resource management and is significant for companies and HR professionals.
Article
Mathematics
Theyazn H. H. Aldhyani, Hasan Alkahtani
Summary: In order to secure IoT networks, deep learning models such as LSTM and CNN-LSTM have been used to construct network intrusion detection systems (NIDSs) for Agriculture 4.0 networks. The proposed model achieved a high level of precision (100%) in detecting various types of DDoS attacks, according to evaluation metrics like precision, recall, F1-score, and accuracy. This model provides a high level of protection against cyber threats in Agriculture 4.0.
Article
Green & Sustainable Science & Technology
Hasan Alkahtani, Theyazn H. H. Aldhyani, Saleh Nagi Alsubari
Summary: Solar power is an excellent alternative energy source that can reduce our dependence on nonrenewable and destructive fossil fuels. Accurate prediction of solar radiation is important for the development of solar energy. Lack of access to reliable data can severely impact the deployment and performance of solar energy systems.
Article
Green & Sustainable Science & Technology
Elham Alzain, Shaha Al-Otaibi, Theyazn H. H. Aldhyani, Ali Saleh Alshebami, Mohammed Amin Almaiah, Mukti E. Jadhav
Summary: In this study, multilayer perceptron and adaptive network-based fuzzy inference system models were used for PV power production forecasting. The suggested method provided better results compared to the latest models, and future PV power generation values were also predicted. The ultimate goal is to achieve a balance between the supply and demand of energy through model predictive control technique.
Article
Green & Sustainable Science & Technology
Ali Alzahrani, Theyazn H. H. Aldhyani
Summary: Online food security and industrial environments, as well as sustainability-related industries, require network traffic analysis for proper security information to prevent attacks. This research proposes a deep learning-based network intrusion detection system for SCADA networks, achieving high accuracy and the ability to handle emerging threats.
Article
Green & Sustainable Science & Technology
Abdullah H. H. Al-Nefaie, Theyazn H. H. Aldhyani
Summary: This study contributes to the field by using advanced artificial intelligence to model and predict vehicle CO2 emissions. The LSTM and BiLSTM models show high accuracy in forecasting, with the BiLSTM model performing the best. The findings provide policymakers with a useful tool for environmental policy-making.
Article
Chemistry, Multidisciplinary
Mohammed Al-Yaari, Tawfik A. Saleh
Summary: Polyethyleneimine-grafted graphene oxide (PEI/GO) was synthesized by using graphene, polyethyleneimine, and trimesoyl chloride. The characterization results confirm the successful synthesis of PEI/GO and its strong interaction with lead (Pb2+) ions. The isotherm study reveals the adsorption process follows the Freundlich isotherm model, with a high maximum adsorption capacity. The prepared PEI/GO adsorbent shows promise for wastewater treatment due to its fast and high uptake removal capacity for Pb2+ ions and other heavy metals.
Article
Chemistry, Multidisciplinary
Hasan Alkahtani, Theyazn H. H. Aldhyani, Mohammed Y. Alzahrani
Summary: People with ASDs struggle with recognizing and engaging with others, and the symptoms can occur in various situations. Developing expert systems that use facial landmarks to identify ASD in children is a significant contribution to improving healthcare in Saudi Arabia. Deep learning algorithms, such as CNNs, are effective for investigating and diagnosing ASDs.
APPLIED SCIENCES-BASEL
(2023)
Article
Computer Science, Information Systems
Theyazn H. H. Aldhyani, Mohammad Ayoub Khan, Mohammed Amin Almaiah, Noha Alnazzawi, Ahmad K. Al Hwaitat, Ahmed Elhag, Rami Taha Shehab, Ali Saleh Alshebami
Summary: Computational intelligence (CI) and artificial intelligence (AI) play important roles in the development of smart and sustainable healthcare systems. However, the widespread use of smart devices for IoT applications generates massive amounts of data and raises concerns about confidentiality. This research aims to prove the efficacy of a secure Internet of Medical Things (IoMT) model in detecting and managing breast cancer using gated recurrent units (GRUs).
Article
Mathematics
Mosleh Hmoud Al-Adhaileh, Amit Verma, Theyazn H. H. Aldhyani, Deepika Koundal
Summary: Potato is an important crop that supports numerous people and contributes to economic growth. However, potato blight is a major destroyer of potato crops worldwide. With the introduction of neural networks, researchers have made contributions to early detection of potato blight using different machine and deep learning algorithms. To address the challenges of accuracy and computation time, a customised convolutional neural network (CNN) was developed, which outperformed other algorithms with 99% accuracy using 839,203 trainable parameters in 183 s of training time.
Retraction
Engineering, Biomedical
T. H. H. Aldhyani
APPLIED BIONICS AND BIOMECHANICS
(2023)
Article
Mathematics
Hasan Alkahtani, Zeyad A. T. Ahmed, Theyazn H. H. Aldhyani, Mukti E. Jadhav, Ahmed Abdullah Alqarni
Summary: Autism spectrum disorder (ASD) can be diagnosed based on the lack of behavioral skills and social communication. This study aims to identify children's abnormal behavior, which might be a sign of autism, using videos recorded in a natural setting. Deep learning video classification methods are utilized to classify self-stimulatory activities and normal behavior in real-time.
Article
Mathematics
Hasan Alkahtani, Theyazn H. H. Aldhyani, Zeyad A. T. Ahmed, Ahmed Abdullah Alqarni
Summary: This study presents a novel methodology for automating the classification of pediatric ADHD using EEG biomarkers through machine learning and deep learning techniques. The proposed system achieved high accuracy in diagnosing ADHD and has the potential for early intervention.