Correction: Oluwasanmi et al. Multi-Head Spatiotemporal Attention Graph Convolutional Network for Traffic Prediction. 2023, , 3836.

In the original publication [...

Cloud-Edge-End Collaborative Federated Learning: Enhancing Model Accuracy and Privacy in Non-IID Environments.

Cloud-edge-end computing architecture is crucial for large-scale edge data processing and analysis. However, the diversity of terminal nodes and task complexity in this architecture often result in non-independent and identically distributed (non-IID) data, making it challenging to balance data heterogeneity and privacy protection. To address this, we propose a privacy-preserving federated learning method based on cloud-edge-end collaboration.

Targeting HBV cccDNA Levels: Key to Achieving Complete Cure of Chronic Hepatitis B.

Chronic hepatitis B (CHB) caused by HBV infection has brought suffering to numerous people. Due to the stable existence of HBV cccDNA, the original template for HBV replication, chronic hepatitis B (CHB) is difficult to cure completely. Despite current antiviral strategies being able to effectively limit the progression of CHB, complete CHB cure requires directly targeting HBV cccDNA.

Design and Implementation of a CMOS-MEMS Out-of-Plane Detection Gyroscope.

A MEMS gyroscope is a critical sensor in attitude control platforms and inertial navigation systems, which has the advantages of small size, light weight, low energy consumption, high reliability and strong anti-interference capability. This paper presents the design, simulation and fabrication of a Y-axis gyroscope with out-of-plane detection developed using CMOS-MEMS technology. The structural dimensions of the gyroscope were optimized through a multi-objective genetic algorithm, and modal, harmonic response and range simulation analyses were carried out to verify the reasonableness of the design.

Study on the Curing Behaviors of Benzoxazine Nitrile-Based Resin Featuring Fluorene Structures and the Excellent Properties of Their Glass Fiber-Reinforced Laminates.

Benzoxazine and o-phthalonitrile resin are two of the most eminent polymer matrices within high-performance fiber-reinforced resin-based composite materials. Studying the influence modalities of their structures and forming processes on performance can furnish a theoretical basis for the design and manufacturing of superior performance composite materials. In this study, we initially incorporated a fluorene structure into the molecular main chain through molecular design to prepare a fluorene-containing benzoxazine nitrile-based resin.

Empirical Comparison and Analysis of Artificial Intelligence-Based Methods for Identifying Phosphorylation Sites of SARS-CoV-2 Infection.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a member of the large coronavirus family with high infectivity and pathogenicity and is the primary pathogen causing the global pandemic of coronavirus disease 2019 (COVID-19). Phosphorylation is a major type of protein post-translational modification that plays an essential role in the process of SARS-CoV-2-host interactions. The precise identification of phosphorylation sites in host cells infected with SARS-CoV-2 will be of great importance to investigate potential antiviral responses and mechanisms and exploit novel targets for therapeutic development.

Modeling and Visual Simulation of Bifurcation Aneurysms Using Smoothed Particle Hydrodynamics and Murray's Law.

Aneurysm modeling and simulation play an important role in many specialist areas in the field of medicine such as surgical education and training, clinical diagnosis and prediction, and treatment planning. Despite the considerable effort invested in developing computational fluid dynamics so far, visual simulation of blood flow dynamics in aneurysms, especially the under-explored aspect of bifurcation aneurysms, remains a challenging issue. To alleviate the situation, this study introduces a novel Smoothed Particle Hydrodynamics (SPH)-based method to model and visually simulate blood flow, bifurcation progression, and fluid-structure interaction.

Predicting Body Weight from Birth to Old Age in Giant Pandas Using Machine Learning.

The giant panda () is one of the animals with the largest body weight differences between its birth and adult stages, where the newborn cub is 0.1% the size of its mother. The rapid growth of panda cubs has been reported previously, but little is known about the growth pattern of their entire lifetime.

Multifractal dynamic changes of spontaneous brain activity in psychiatric disorders: Adult attention deficit-hyperactivity disorder, bipolar disorder, and schizophrenia.

It is one of the strategies to study the complexity of spontaneous fluctuation of brain neurons based on resting-state functional magnetic resonance imaging (rs-fMRI), but the multifractal characteristics of spontaneous fluctuation of brain neurons in psychiatric diseases need to be studied. Therefore, this paper will study the multifractal spontaneous brain activity changes in psychiatric disorders using the multifractal detrended fluctuation analysis algorithm based on the UCLA datasets. Specifically: (1) multifractal characteristics in adult attention deficit-hyperactivity disorder (ADHD), bipolar disorder (BP), and schizophrenia (SCHZ); (2) the source of those multifractal characteristics.

IFN alpha signaling drives hematopoietic stem cells malfunction under acute inflammation.

Inflammation stimulation regulates the activity of hematopoietic stem cells (HSCs) through direct-sensing and cytokine-mediation. It is known that HSCs directly sense lipopolysaccharide (LPS), a classical infection-related inflammatory signal, via toll like receptor 4 (TLR4) and subsequently become active. However, the mechanism underlying the activity change of HSCs induced by LPS remains incompletely disclosed.

Spontaneous Catalytic Reaction of a Surfactant in the Interfacial Microenvironment of Colloidal Gold Nanoparticles.

The performance of nanomaterials is significantly determined by the interfacial microenvironment, in which a surfactant plays an essential role as the adsorbent, but its involvement in the interfacial reaction is often overlooked. Here, it was discovered that citrate and ascorbic acid, the two primarily used surfactants for colloidal gold nanoparticles (Au NPs), can spontaneously undergo catalytic reaction with trace-level nitrogenous residue under ambient environment to form oxime, which is subsequently cleaved to generate CN or a compound containing the -CN group. Such a catalytic reaction shows wide universality in both reactants, including various carbonaceous and nitrogenous sources, and metal catalysts, including Au, Ag, Fe, Cu, Ni, Pt, and Pd NPs.

Characterization of 3,3'-iminodipropionitrile (IDPN) damaged utricle transcriptome in the adult mouse utricle.

Utricle is an important vestibular sensory organ for maintaining balance. 3,3'-iminodipropionitrile (IDPN), a prototype nitrile toxin, has been reported to be neurotoxic and vestibulotoxic, and can be used to establish an damage model of vestibular dysfunction. However, the mechanism of utricular HCs damage caused by IDPN is unclear.

Complexity of social media in the era of generative AI.

The article presents a perspective on how the emerging generative AI technology can shape social media and the new challenges in studying social media in this generative.

Integrating machine learning with bioinformatics for predicting idiopathic pulmonary fibrosis prognosis: developing an individualized clinical prediction tool.

Idiopathic pulmonary fibrosis (IPF) is a chronic interstitial lung disease with a poor prognosis. Its non-specific clinical symptoms make accurate prediction of disease progression challenging. This study aimed to develop molecular-level prognostic models to personalize treatment strategies for IPF patients.

Coupling Nitrate-to-Ammonia Conversion and Sulfion Oxidation Reaction Over Hierarchical Porous Spinel MFeO (M═Ni, Co, Fe, Mn) in Wastewater.

The construction of coupled electrolysis systems utilizing renewable energy sources for electrocatalytic nitrate reduction and sulfion oxidation reactions (NORR and SOR), is considered a promising approach for environmental remediation, ammonia production, and sulfur recovery. Here, a simple chemical dealloying method is reported to fabricate a hierarchical porous multi-metallic spinel MFeO (M═Ni, Co, Fe, Mn) dual-functional electrocatalysts consisting of Mn-doped porous NiFeO/CoFeO heterostructure networks and Ni/Co/Mn co-doped FeO nanosheet networks. The excellent NORR with high NH Faradaic efficiency of 95.

Unlocking the potential of photobiomodulation therapy for brain neurovascular coupling: The biological effects and medical applications.

Photobiomodulation (PBM) therapy stands as an innovative neurostimulation modality that has demonstrated both efficacy and safety in improving brain function. This therapy exerts multifaceted influences on neurons, blood vessels, and their intricate interplay known as neurovascular coupling (NVC). Growing evidence indicates that NVC may present a promising target for PBM intervention.

Buried Interface Modulation Using Self-Assembled Monolayer and Ionic Liquid Hybrids for High-Performance Perovskite and Perovskite/CuInGaSe Tandem Photovoltaics.

Effective modifications for the buried interface between self-assembled monolayers (SAMs) and perovskites are vital for the development of efficient, stable inverted perovskite solar cells (PSCs) and their tandem photovoltaics. Herein, an ionic-liquid-SAM hybrid strategy is developed to synergistically optimize the uniformity of SAMs and the crystallization of perovskites above. Specifically, an ionic liquid of 1-butyl-3-methyl-1H-imidazol-3-iumbis((trifluoromethyl)sulfonyl)amide (BMIMTFSI) is incorporated into the SAM solution, enabling reduced surface roughness, improved wettability, and a more evenly distributed surface potential of the SAM film.

Anomalous drainage of lingular vein into left inferior pulmonary vein during thoracoscopic lung cancer surgery.

Background: The intricate anatomical variations in lung structure often perplex thoracic surgeons, and the accurate identification of these variations is closely associated with favorable surgical outcomes.

Case Presentation: A 53-year-old female patient who underwent computed tomography (CT) examination due to chest discomfort, revealing the presence of a partial solid nodule highly suspected of early-stage lung cancer, measuring approximately 2.8 × 2.

Global, regional, and national burden of esophageal cancer: a systematic analysis of the Global Burden of Disease Study 2021.

Background And Objective: Esophageal cancer (EC) is the seventh most prevalent cancer globally and the sixth leading cause of cancer-related mortality. This study aimed to provide an updated stratified assessment of rates in EC incidence, mortality, and disability-adjusted life-years (DALYs) from 1990 to 2021 by sex, age, and Socio-demographic Index (SDI) at global, regional, and national levels, as well as to project the future trends of EC both globally and regionally.

Methods: Data about age-standardized rates (ASRs) of incidence (ASIR), mortality (ASDR), probability of death (ASPoD) and DALYs (ASDALYRs) of EC were obtained from the 2021 Global Burden of Disease (GBD) study.

Concomitant medication effects on patients with lung cancer taking immune checkpoint inhibitors a review.

In the past decade, a variety of immune checkpoint inhibitors (ICIs) are currently approved for lung cancer in the world. As a new therapeutic approach, ICIs have shown significant clinical benefits in the first-line or second-line treatment for advanced lung cancer, improving the survival and quality of life of patients. Patients need to take multiple drugs in the meantime due to their own disease or side effects during treatment.

Machine learning Nomogram for Predicting endometrial lesions after tamoxifen therapy in breast Cancer patients.

Objective Endometrial lesions are a frequent complication following breast cancer, and current diagnostic tools have limitations. This study aims to develop a machine learning-based nomogram model for predicting the early detection of endometrial lesions in patients. The model is designed to assess risk and facilitate individualized treatment strategies for premenopausal breast cancer patients.

Putative epicenters identified by transcriptome-neuromorphic interactions in attention-deficit/hyperactivity disorder biotypes.

Attention-deficit hyperactivity disorder (ADHD) is a heterogenous behavioral disorder with inattention, hyperactivity and impulsivity symptoms, indicating the important implication of identifying biotypes and its epicenters in understanding disease's pathogenesis. The study investigated the neuromorphic heterogeneity relating to transcriptional similarity architecture in ADHD, and further analyzed the epicenters of network-spreading in each ADHD biotype and their correlations with clinical characteristics. Individuals with ADHD could be identified into two discriminative biotypes that exhibited distinct neuromorphic aberrances.