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A Multi-Modal Three-Channel Bearing Fault Diagnosis Method Based on CNN Fusion Attention Mechanism Under Strong Noise Conditions
Yingyong Zou
,Chunfang Li
,Yu Zhang
,Zhiqiang Si
,Long Li
As a core component of mechanical equipment, the operational status of bearings directly determines equipment safety, making early fault diagnosis critically important. However, bearing vibration signals are susceptible to substantial noise interference and exhibit both nonlinear and non-stationary characteristics, rendering traditional single-mode diagnostic methods ineffective at extracting fault features. Therefore, this paper proposes a three-channel multimodal fault diagnosis network (M-CNNBiAM) integrated with a convolutional autoencoder (CAE). Based on a convolutional neural network (CNN) architecture, this network employs CAE for signal denoising, utilizes continuous wavelet transform (CWT) to construct time-frequency features, and incorporates dual enhancement modules: convolutional attention (CBAM) and window attention (S-W-MSA).On one hand, it extracts complementary features from the raw vibration signal and the wavelet transform frequency domain signal, fusing them at the channel dimension. On the other hand, it embeds Shifted Window Attention (SW-MSA) and Window Self-Attention (W-MSA) between convolutional layers to capture global-local features. Combined with CBAM to enhance fault location attention, it mitigates the vanishing gradient problem through residual connections, enabling the extraction of frequency domain features. To address the characteristics of one-dimensional time-series signals, a bidirectional gated recurrent unit (BiGRU) is introduced to collaborate with CNN for extracting temporal features. Experiments demonstrate that on the West China University public dataset and self-test dataset, M-CNNBiAM achieves an average diagnostic accuracy of 95.84% under -10dB high-noise conditions, outperforming comparative methods and validating its superior performance in complex noise environments.
As a core component of mechanical equipment, the operational status of bearings directly determines equipment safety, making early fault diagnosis critically important. However, bearing vibration signals are susceptible to substantial noise interference and exhibit both nonlinear and non-stationary characteristics, rendering traditional single-mode diagnostic methods ineffective at extracting fault features. Therefore, this paper proposes a three-channel multimodal fault diagnosis network (M-CNNBiAM) integrated with a convolutional autoencoder (CAE). Based on a convolutional neural network (CNN) architecture, this network employs CAE for signal denoising, utilizes continuous wavelet transform (CWT) to construct time-frequency features, and incorporates dual enhancement modules: convolutional attention (CBAM) and window attention (S-W-MSA).On one hand, it extracts complementary features from the raw vibration signal and the wavelet transform frequency domain signal, fusing them at the channel dimension. On the other hand, it embeds Shifted Window Attention (SW-MSA) and Window Self-Attention (W-MSA) between convolutional layers to capture global-local features. Combined with CBAM to enhance fault location attention, it mitigates the vanishing gradient problem through residual connections, enabling the extraction of frequency domain features. To address the characteristics of one-dimensional time-series signals, a bidirectional gated recurrent unit (BiGRU) is introduced to collaborate with CNN for extracting temporal features. Experiments demonstrate that on the West China University public dataset and self-test dataset, M-CNNBiAM achieves an average diagnostic accuracy of 95.84% under -10dB high-noise conditions, outperforming comparative methods and validating its superior performance in complex noise environments.
Posted: 14 January 2026
Sandplay Therapy with Suicidal Ideation and Self-Injury–Focused Engagement (SPT-SAFE) for Adolescents: An Exploratory Early Cohort Analysis of an Ongoing Randomized Controlled Trial
HyeonJeong Kwak
,UnKyoung Ahn
Posted: 14 January 2026
Info-Computation and Observer-Dependence in Quantum
Gordana Dodig-Crnkovic
Posted: 14 January 2026
Quantum Information Copy Time and Gravity from Relative-Entropy Sources: Global Manuscript with Microscopic Control and Reproducible Artefacts
Mohamed Sacha
Posted: 14 January 2026
Advancing Electronic Records Management Systems: Comparative Strategies, Challenges, and Implementation Insights
Darron Rodan John
,Fang-Ming Hsu
,Yuh-Jia Chen
Posted: 14 January 2026
Responsibility, Habit, and Control: Digital Humanismand the Delegation of Critical Functions toIntelligent Autonomous Systems
Gordana Dodig-Crnkovic
Posted: 14 January 2026
Continuity: An Ontological Proposal for the Mind-Body Problem
Jae Lee
Posted: 14 January 2026
Bayesian Forward Design Methodology for Laminar Transonic Airfoils with Cross Flow Attenuation at Large Sweep Angles
Samarth Kakkar
,Thomas Streit
,Arne Seitz
,Rolf Radespiel
Posted: 14 January 2026
Does GDP Buy Perceived Urban Health? Evidence from China’s Urban Physical Examination Survey
Cai Jincheng
,He Ju
Posted: 14 January 2026
Democratizing Urban Well-being: A Virtual Reality and Eye-Tracking Analysis of Biophilic Interventions Across Socioeconomic Contexts
Cleiton Ferreira
,Marina Guil-Jiménez
,Paula Latorre
,Aurora Molina-Muñoz
,Sergio Castaño-Castaño
,Francisco Nieto-Escamez
Posted: 14 January 2026
Muno-IgY Supplementation Improves Respiratory Health, Immune Response, and Exercise-Induced Physiological Stress in Healthy Adults: A Randomized Controlled Pilot Study
Shahna Fathima
,Paul E. Kilgore
,Tina Sarkar
,Navneet Sharma
,Huan H. Nguyen
Posted: 14 January 2026
It Takes Two to Tango: SARS-CoV-2 and Influenza Co-Circulation and Co-Vaccination
Mohammad Kamransarkandi
,Elena A. Varyushina
,Andrey N. Gorshkov
,Marina A. Stukova
Posted: 14 January 2026
The Prevention Theorem: Time-Dependent Constraints on Post-Exposure Prophylaxis for HIV
A.C. Demidont
Posted: 14 January 2026
Youth Unemployment & Job Crisis: A Situation Analysis and Way Forward
Anika Tasnim
Posted: 14 January 2026
Beyond Handgrip—Trunk Strength, Gait Speed, Resting Metabolic Rate, and Muscle Mass as Integrated Predictors of Sarcopenia in Brazilian Older Women: A Pilot Observational Study
Lucas Ferreira de Souza Campos
,Juliana de Alcantara Silva Fonseca
,Ana Clara de Souza Oliveira
,Guilherme Moreira
,Leonardo de Souza Correa
,Pedro Henrique de Almeida Louza
,Ana Carolina Dutra Tavares
,Luana Lopes de Souza
,Raquel Carvalho Castiglione
,Hércules Rezende Freitas
+1 authors
Sarcopenia is a complex condition marked by reductions in muscle strength, mass, and overall physical performance, which has significant consequences for functional autonomy and metabolic health in elderly women. This study sought to examine the correlations between lower limb strength, functional capabilities, and metabolic indicators in community-dwelling older women categorized according to the EWGSOP2 criteria. A total of thirty-eight women aged ≥ 60 years underwent assessments, including anthropometric, hemodynamic, and metabolic evaluations, along with functional tests such as handgrip strength, chair-rise test, gait speed, Timed Up-and-Go, and maximal isometric hip extension strength (MIHE). The criteria for probable sarcopenia were established using the handgrip thresholds set by the EWGSOP2. Women identified as having probable sarcopenia displayed markedly lower MIHE, diminished gait speed, inferior performance in chair-rise and Timed Up-and-Go tests, decreased muscle mass, and a lower resting metabolic rate than their non-sarcopenic counterparts. MIHE exhibited robust correlations with muscle mass, resting metabolic rate, and functional performance metrics. These results suggest that assessments of lower limb and trunk strength yield pertinent insights beyond handgrip strength alone. Function-oriented evaluations may improve sarcopenia screening and facilitate the identification of older women at risk of functional and metabolic deficiencies in community-based environments.
Sarcopenia is a complex condition marked by reductions in muscle strength, mass, and overall physical performance, which has significant consequences for functional autonomy and metabolic health in elderly women. This study sought to examine the correlations between lower limb strength, functional capabilities, and metabolic indicators in community-dwelling older women categorized according to the EWGSOP2 criteria. A total of thirty-eight women aged ≥ 60 years underwent assessments, including anthropometric, hemodynamic, and metabolic evaluations, along with functional tests such as handgrip strength, chair-rise test, gait speed, Timed Up-and-Go, and maximal isometric hip extension strength (MIHE). The criteria for probable sarcopenia were established using the handgrip thresholds set by the EWGSOP2. Women identified as having probable sarcopenia displayed markedly lower MIHE, diminished gait speed, inferior performance in chair-rise and Timed Up-and-Go tests, decreased muscle mass, and a lower resting metabolic rate than their non-sarcopenic counterparts. MIHE exhibited robust correlations with muscle mass, resting metabolic rate, and functional performance metrics. These results suggest that assessments of lower limb and trunk strength yield pertinent insights beyond handgrip strength alone. Function-oriented evaluations may improve sarcopenia screening and facilitate the identification of older women at risk of functional and metabolic deficiencies in community-based environments.
Posted: 14 January 2026
MnZnFe2O4@SrWO4 Ceramic Composite as an Efficient Non-Noble Electrocatalyst for the Oxygen Evolution Reaction in Alkaline Media
Irum Jamil
,Faisal Nawaz
,Muqdssa Rashid
,V. Geethalakshmi
,Hsien-Yi Hsu
,Mohammed-Ibrahim Jamesh
The development of efficient, earth abundant electrocatalysts for the oxygen evolution reaction (OER) is essential for alkaline water electrolysis. In this work, we prepared MnZnFe₂O₄, SrWO₄, and a MnZnFe₂O₄@SrWO₄ ferrite–tungstate heterostructure by simple co-precipitation and hydrothermal routes and evaluated them as OER catalysts in 1 M KOH. The catalysts are characterized by XRD, UV–Vis, FTIR, SEM, and EDX. The catalysts exhibit phase-pure components with intimate contact between the two phases, and a smaller particle size for the composite. The MnZnFe₂O₄@SrWO₄ exhibits modified electronic structure possibly due to the electronic interaction between Fe and W centers. Electrochemical measurements demonstrated an overpotential of 200 mV at 10 mA cm-2, that exhibits a reduced Tafel slope (150 mV dec⁻¹), and displays lower charge-transfer resistance than the single-phase oxides. In addition, the composite retains >94% of its current over 24 h, indicating good durability. These results suggest that ferrite–tungstate coupling can be an effective strategy to non-noble OER catalysts.
The development of efficient, earth abundant electrocatalysts for the oxygen evolution reaction (OER) is essential for alkaline water electrolysis. In this work, we prepared MnZnFe₂O₄, SrWO₄, and a MnZnFe₂O₄@SrWO₄ ferrite–tungstate heterostructure by simple co-precipitation and hydrothermal routes and evaluated them as OER catalysts in 1 M KOH. The catalysts are characterized by XRD, UV–Vis, FTIR, SEM, and EDX. The catalysts exhibit phase-pure components with intimate contact between the two phases, and a smaller particle size for the composite. The MnZnFe₂O₄@SrWO₄ exhibits modified electronic structure possibly due to the electronic interaction between Fe and W centers. Electrochemical measurements demonstrated an overpotential of 200 mV at 10 mA cm-2, that exhibits a reduced Tafel slope (150 mV dec⁻¹), and displays lower charge-transfer resistance than the single-phase oxides. In addition, the composite retains >94% of its current over 24 h, indicating good durability. These results suggest that ferrite–tungstate coupling can be an effective strategy to non-noble OER catalysts.
Posted: 14 January 2026
A DNA Vaccine Incorporating the MHC Class I Trafficking Domain and PADRE Epitope Enhances Antitumor Immunity in a Murine Pancreatic Cancer Model
Simiao Cao
,Guoxuan Bai
,Qimuge Wuri
,Jiayin Li
,Xiaojing Zhang
,Zhilin Han
,Hui Wu
,Jiaxin Wu
,Chu Wang
,Xianghui Yu
+1 authors
Posted: 14 January 2026
Naringenin Ameliorates LPS-Induced Neuroinflammation Through NF-κB Signaling in Human Microglia and Protects Neuronal Cells
Shahzada Mudasir Rashid
,Antonisamy William James
,Faheem Shehjar
,Shahd Yousuf
,Zahoor A. Shah
Posted: 14 January 2026
Atrial Fibrillation and Cognitive Decline: A Comprehensive Review of Pathophysiological Mechanisms, Therapeutic Strategies, and Digital Health Technologies in Neuroprotection
Amparo Santamaria
,Cristina Antón
,Nataly Ibarra
,María Fernández
,Pedro González
,Rafael Carrasco
Background: Atrial fibrillation (AF) is independently associated with cognitive impairment and dementia through mechanisms extending far beyond traditional cardioembolic stroke risk. However, the relative contribution of distinct pathophysiological pathways and the efficacy of emerging therapeutic interventions for cognitive protection remain incompletely characterized. Objectives: This comprehensive review synthesizes current evidence on the epidemiology, pathophysiological mechanisms, therapeutic interventions (pharmacological, rhythm-control, and digital health), and research priorities addressing the AF–dementia relationship. Methods: A narrative review integrating evidence from observational studies, mechanistic research, randomized controlled trials, systematic reviews, and meta-analyses published through January 2026. Literature sources included MEDLINE/PubMed, major cardiology and neurology journals, and expert consensus statements. Searches used combinations of keywords: "atrial fibrillation," "cognitive decline," "dementia," "silent cerebral infarction," "cerebral hypoperfusion," "direct oral anticoagulants," "catheter ablation," and "digital health." Inclusion criteria encompassed studies examining the AF–cognition association, mechanistic pathways, therapeutic interventions with cognitive outcomes, and digital health technologies in AF management. Heterogeneous study designs prevented quantitative meta-analysis; qualitative synthesis focused on effect sizes, strength of evidence, and clinical implications. Results: Strong epidemiological evidence demonstrates that AF increases relative risk of dementia by 1.4–2.2 fold independently of clinical stroke, with silent cerebral infarction present in 25–40% of AF patients. Multiple interacting pathophysiological mechanisms account for AF-associated cognitive decline: cerebral microembolism (meta-analysis: OR 2.30 for silent infarction on MRI), chronic cerebral hypoperfusion (15–20% reduction in total cerebral blood flow in persistent AF), neuroinflammation, cerebral small vessel disease, and structural brain atrophy. Emerging therapeutic strategies offer complementary neuroprotective mechanisms: direct oral anticoagulants (DOACs)—particularly apixaban and rivaroxaban—reduce dementia risk by approximately 30% compared to warfarin (RR 0.69); rhythm control strategies and catheter ablation demonstrate dementia risk reduction (HR 0.52–0.69); and comprehensive digital health platforms implementing the ABC pathway reduce adverse cardiovascular events by 61% while optimizing adherence and enabling early AF detection. However, evidence-specific to cognitive endpoints remains limited, with the landmark BRAIN-AF trial showing no benefit of low-dose rivaroxaban in low-stroke-risk AF patients—suggesting that non-embolic mechanisms predominate in this population. Conclusions: AF represents a multifaceted threat to brain health requiring a paradigm shift from isolated stroke prevention toward comprehensive heart–brain health optimization. Integration of pharmacological neuroprotection (preferring DOACs), hemodynamic optimization (rhythm control in selected patients), cardiovascular risk factor management, and digital health technologies provides unprecedented opportunity for cognitive preservation. However, critical knowledge gaps persist regarding AF burden thresholds, the relative contribution of competing pathophysiological mechanisms, optimal anticoagulation strategies in low-risk populations, and the long-term cognitive benefits of emerging digital technologies. Prospective randomized clinical trials with cognitive impairment as a primary endpoint, serial neuroimaging, and diverse population representation are urgently needed to validate preventive strategies and refine therapeutic decision-making.
Background: Atrial fibrillation (AF) is independently associated with cognitive impairment and dementia through mechanisms extending far beyond traditional cardioembolic stroke risk. However, the relative contribution of distinct pathophysiological pathways and the efficacy of emerging therapeutic interventions for cognitive protection remain incompletely characterized. Objectives: This comprehensive review synthesizes current evidence on the epidemiology, pathophysiological mechanisms, therapeutic interventions (pharmacological, rhythm-control, and digital health), and research priorities addressing the AF–dementia relationship. Methods: A narrative review integrating evidence from observational studies, mechanistic research, randomized controlled trials, systematic reviews, and meta-analyses published through January 2026. Literature sources included MEDLINE/PubMed, major cardiology and neurology journals, and expert consensus statements. Searches used combinations of keywords: "atrial fibrillation," "cognitive decline," "dementia," "silent cerebral infarction," "cerebral hypoperfusion," "direct oral anticoagulants," "catheter ablation," and "digital health." Inclusion criteria encompassed studies examining the AF–cognition association, mechanistic pathways, therapeutic interventions with cognitive outcomes, and digital health technologies in AF management. Heterogeneous study designs prevented quantitative meta-analysis; qualitative synthesis focused on effect sizes, strength of evidence, and clinical implications. Results: Strong epidemiological evidence demonstrates that AF increases relative risk of dementia by 1.4–2.2 fold independently of clinical stroke, with silent cerebral infarction present in 25–40% of AF patients. Multiple interacting pathophysiological mechanisms account for AF-associated cognitive decline: cerebral microembolism (meta-analysis: OR 2.30 for silent infarction on MRI), chronic cerebral hypoperfusion (15–20% reduction in total cerebral blood flow in persistent AF), neuroinflammation, cerebral small vessel disease, and structural brain atrophy. Emerging therapeutic strategies offer complementary neuroprotective mechanisms: direct oral anticoagulants (DOACs)—particularly apixaban and rivaroxaban—reduce dementia risk by approximately 30% compared to warfarin (RR 0.69); rhythm control strategies and catheter ablation demonstrate dementia risk reduction (HR 0.52–0.69); and comprehensive digital health platforms implementing the ABC pathway reduce adverse cardiovascular events by 61% while optimizing adherence and enabling early AF detection. However, evidence-specific to cognitive endpoints remains limited, with the landmark BRAIN-AF trial showing no benefit of low-dose rivaroxaban in low-stroke-risk AF patients—suggesting that non-embolic mechanisms predominate in this population. Conclusions: AF represents a multifaceted threat to brain health requiring a paradigm shift from isolated stroke prevention toward comprehensive heart–brain health optimization. Integration of pharmacological neuroprotection (preferring DOACs), hemodynamic optimization (rhythm control in selected patients), cardiovascular risk factor management, and digital health technologies provides unprecedented opportunity for cognitive preservation. However, critical knowledge gaps persist regarding AF burden thresholds, the relative contribution of competing pathophysiological mechanisms, optimal anticoagulation strategies in low-risk populations, and the long-term cognitive benefits of emerging digital technologies. Prospective randomized clinical trials with cognitive impairment as a primary endpoint, serial neuroimaging, and diverse population representation are urgently needed to validate preventive strategies and refine therapeutic decision-making.
Posted: 14 January 2026
A Novel FEC Implementation for VSAT Terminals Using High-Level Synthesis
Najmeh Khosroshahi
,Ron Mankarious
,M. Reza Soleymani
Posted: 14 January 2026
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