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Publisher Correction: Impaired MC3T3-E1 osteoblast differentiation triggered by oncogenic HRAS is rescued by the farnesyltransferase inhibitor Tipifarnib

Exploring the longitudinal dynamics of self-criticism, self-compassion, psychological flexibility, and mental health in a three-wave study

Abstract Self-compassion has been emphasized in its association with reducing anxiety, narcissism, and self-criticism. At the same time, self-judgment as the counter side of self-kindness tends to interchange with the description of self-criticism, which can lead to potential stress and mental illness. Meanwhile, psychological flexibility enhanced through Acceptance and Commitment Therapy (ACT) emerges and is engaged as a therapeutic action after self-compassion. Hence, based on The Transactional Model of Stress and Coping, this three-wave longitudinal study examined longitudinal connections between (1) cognitive appraisal – self-criticism (comparative self-criticism and internalized self-criticism); (2) coping – self-compassion and psychological flexibility (acceptance and action), and (3) outcome – mental health. Regarding the results, at baseline, 412 participants (M age = 39.73, SD = 12.75; 83% female) were enrolled; follow-up rates were 56% at 6 months and 28%(N=115, M age = 40.88, SD = 13.00, 78.3% female) at 12 months. Using the Repeated Measures Panel Analysis Framework, the model investigation with the good fit model index supports the hypothesized pathways based on the Transactional Model of Stress and Coping. Self-compassion and psychological flexibility have been examined to be consistent and stable coping strategies negatively associated with self-criticism. Hence, the current study outcome serves as a theoretical foundation that supports the development of the intervention, evidenced by the potential mediating role or function of self-compassion or compassion-focused therapy and enhancing psychological flexibility through acceptance and commitment therapy.

The unique relationship between body mass index and metabolic syndrome in AIDS patients

Identification of potential SARS-CoV-2 inhibitors among well-tolerated drugs using drug repurposing and in vitro approaches

HarSoNet: a two-stage point cloud registration method integrating soft and hard matching

High expression of ITGB3 ameliorates asthma by inhibiting epithelial-mesenchymal transformation through suppressing the activation of NF-kB pathway

Effects of cigarette smoke extract on angiogenesis and aromatase activity in KGN cells

Anxiety and depression in healthcare workers 2 years after COVID-19 infection and scale validation

The effects of repeated fecal transplantation and activated charcoal treatment on gut dysbiosis induced by concurrent ceftriaxone administration in mice

Heterogeneous update processes shape information cascades in social networks

Surgically induced astigmatism and refractive outcomes after minimally invasive glaucoma surgery combined with cataract surgery

Quantum global minimum finder based on variational quantum search

Abstract The search for global minima is a critical challenge across multiple fields including engineering, finance, and artificial intelligence, particularly with non-convex functions that feature multiple local optima, complicating optimization efforts. We introduce the Quantum Global Minimum Finder (QGMF), an innovative quantum computing approach that efficiently identifies global minima. QGMF combines binary search techniques to shift the objective function to a suitable position and then employs Variational Quantum Search to precisely locate the global minimum within this targeted subspace. Designed with a O(n)-depth circuit architecture, QGMF also utilize the logarithmic benefits of binary search to enhance scalability and efficiency. This work demonstrates the impact of QGMF in advancing the capabilities of quantum computing to overcome complex non-convex optimization challenges effectively.

Efficient control of spider-like medical robots with capsule neural networks and modified spring search algorithm

Selective power transmission using a shift in resonant frequency due to the transportation of liquid metal droplets

Healthcare utilization among Japanese older adults during later stage of prolonged pandemic

Computer aided study on cyclic tetrapeptide based ligands as potential inhibitors of Proplasmepsin IV

Regarding the possible impact of forest fires on the radioactive pollution of groundwater in the chornobyl exclusion zone

Enhancing medical text classification with GAN-based data augmentation and multi-task learning in BERT

Characterization of lactylation-based phenotypes and molecular biomarkers in sepsis-associated acute respiratory distress syndrome

Analysis of control and computational strategies for green energy integration for sociotechnical ecological power infrastructure in Indian and African markets

Abstract The rapid expansion of energy infrastructure in emerging economies, particularly in India and Africa, necessitates advanced control and computational strategies to ensure the seamless integration of green energy resources with conventional power systems. This study conducts a comprehensive analysis of state-of-the-art control mechanisms and optimization techniques for hybrid power networks, focusing on enhancing grid stability, frequency regulation, and resilience under dynamic loading and climatic variations. It explores advanced generation control strategies, including adaptive and predictive control frameworks, to mitigate the inherent intermittency of renewable energy sources. Furthermore, the paper examines multi-objective optimization methodologies for energy dispatch, frequency stabilization, and reliability enhancement in multi-entity power networks. By proposing a robust and computationally efficient framework for hybrid energy integration, this study contributes to the development of resilient, self-sustaining power systems crucial for ensuring long-term energy security, operational efficiency, and economic growth in rapidly developing regions.