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The role of user participation and psychological distance in consumer brand attitudes in gamified marketing
Alendronate partially rescues the periodontal defects in OIM mouse model of osteogenesis imperfecta
AbstractOsteogenesis imperfecta (OI) is a fairly common generalized connective disorder characterized by low bone mass, bone deformities and impaired bone quality that predisposes affected individuals to musculoskeletal fragility. Periodontal ligament (PDL)-alveolar bone and PDL-cementum entheses’ roles under OI conditions during physiological loading and orthodontic forces remain largely unknown. In addition, bisphosphonates (e.g., alendronate) are commonly used therapeutics for the treatment of OI. Our knowledge, in terms of the affects of alendronate treatment on the PDL entheses in OI is also far from complete. In this study, we identified craniofacial skeletal defects in an osteogenesis imperfecta (oim) murine model of OI. Relative to wild-type littermates, oim mice were found to have decreased skull length, cranial height/width/length, nose length, nasal length, and frontal length. Next, we discovered that oim mice exhibited defects in several dental structures, including short roots and decreased volumes of the alveolar bone, dentin, and cellular cementum. Further, we specifically investigated periodontal defects in the oim mice. Alveolar bone loss in oim mice was primarily associated with elevated bone resorption due to an increased osteoclast number, along with reduced bone formation related to increased sclerostin (SOST) expression. PDL fibers in oim mice were disrupted and discontinuous, while Sharpey’s fibers at the PDL-bone entheses were reduced. Mechanism-based studies showed that catabolism of the PDL was elevated in oim mice, as revealed by an increase in MMP13 and CTSK expression. Meanwhile, the quality of the collagen fibers were impaired in oim mice due to a large accumulation of uncleaved collagen I fibers. With alendronate treatment, however, we could partially rescue these phenotypes. This study, for the first time, characterized periodontal defects in oim mice, detailed craniofacial defects and demonstrated the effectiveness of alendronate in partially restoring these defects.
Formation of individual stripes in a mixed-dimensional cold-atom Fermi–Hubbard system
AbstractThe relation between d-wave superconductivity and stripes is fundamental to the understanding of ordered phases in high-temperature cuprate superconductors1–6. These phases can be strongly influenced by anisotropic couplings, leading to higher critical temperatures, as emphasized by the recent discovery of superconductivity in nickelates7–10. Quantum simulators with ultracold atoms provide a versatile platform to engineer such couplings and to observe emergent structures in real space with single-particle resolution. Here we show, to our knowledge, the first signatures of individual stripes in a cold-atom Fermi–Hubbard quantum simulator using mixed-dimensional (mixD) settings. Increasing the energy scale of hole–hole attraction to the spin exchange energy, we access the interesting crossover temperature regime in which stripes begin to form11. We observe extended, attractive correlations between hole dopants and find an increased probability of forming larger structures akin to individual stripes. In the spin sector, we study correlation functions up to the third order and find results consistent with stripe formation. These observations are interpreted as a precursor to the stripe phase, which is characterized by interleaved charge and spin density wave ordering with fluctuating lines of dopants separating domains of opposite antiferromagnetic order12–14.
2D MoS2-based reconfigurable analog hardware
Transition metal vacancy and position engineering enables reversible anionic redox reaction for sodium storage
What are the hidden shortcomings of balance training research in older adults that prevent its transfer into practice? Scoping review
Background Although a lot of attention is paid to the flaws of balance training research in older adults, the low methodological quality and incomplete reporting of studies still limit the knowledge transfer between research and practice. These known shortcomings are considered also as barriers for creating recommendations for balance training in older adults. Despite the considerable efforts to improve the scientific quality of studies, such recommendations have not yet been formulated to date. Therefore, this scoping review aims (1) to analyze the literature that addresses balance training in older adults, (2) to identify and summarize gaps in the existing literature, and (3) to propose future research on this topic. Methods We focused on studies that evaluated the effect of balance training on balance control in apparently healthy older adults over 60 years of age. Results Out of 6910 potentially relevant studies, only 26 met the eligibility criteria. The identified shortcomings were as follows: missing a priori criteria for training session attendance and leisure-time physical activities, insufficiently described exercises and training load, and inappropriately chosen tests. Conclusions Among the shortcomings of the balance training research, the insufficiently described balance training program and inappropriately chosen tests can be considered the most important. For this reason, even with an excellently designed experiment, it is almost impossible for practitioners to apply the results of such studies into practice. Therefore, researchers should pay more attention to possible users of the acquired knowledge, which is more than desirable in the case of exercise programs for older adults.
Enhancing Persian text summarization through a three-phase fine-tuning and reinforcement learning approach with the mT5 transformer model
Protective effect of compound K against podocyte injury in chronic kidney disease by maintaining mitochondrial homeostasis
Neuromodulation of risk and reward processing during decision making in individuals with general anxiety disorder (GAD)
Demonstration of high-reconfigurability and low-power strong physical unclonable function empowered by FeFET cycle-to-cycle variation and charge-domain computing
Overcoming optical losses in thin metal-based recombination layers for efficient n-i-p perovskite-organic tandem solar cells
AbstractPerovskite-organic tandem solar cells (P-O-TSCs) hold substantial potential to surpass the theoretical efficiency limits of single-junction solar cells. However, their performance is hampered by non-ideal interconnection layers (ICLs). Especially in n-i-p configurations, the incorporation of metal nanoparticles negatively introduces serious parasitic absorption, which alleviates photon utilization in organic rear cell and decisively constrains the maximum photocurrent matching with front cell. Here, we demonstrate an efficient strategy to mitigate optical losses in Au-embedded ICLs by tailoring the shape and size distribution of Au nanoparticles via manipulating the underlying surface property. Achieving fewer, smaller, and more uniformly spherical Au nanoparticles significantly minimizes localized surface plasmon resonance absorption, while maintaining efficient electron-hole recombination within ICLs. Consequently, optimized P-O-TSCs combining CsPbI2Br with various organic cells benefit from a substantial current gain of >1.5 mA/cm2 in organic rear cells, achieving a champion efficiency of 25.34%. Meanwhile, optimized ICLs contribute to improved long-term device stability.
Substance use and disordered eating risk among college students with obsessive-compulsive conditions
Purpose College students are at higher risk for problematic substance use and disordered eating. Few studies have examined the comorbid risks associated with OCD despite the increased prevalence of OCD among young adults. This study examined substance use and disordered eating risk associated with OCD conditions among college students and how this association may vary by sex/gender. Methods Data were from 92,757 undergraduate students aged 18–24 enrolled in 216 colleges between Fall 2021 and Fall 2022, from the American College Health Association-National College Health Assessment III. Regression models were used to estimate alcohol, cannabis, tobacco, and disordered eating risk among those with OCD related conditions compared to those without conditions, overall and by sex/gender, while adjusting for covariates and school clustering. Results Students with OCD conditions displayed a higher prevalence of substance use and disordered eating risks. In adjusted models, OCD conditions were associated with increased odds of moderate/high tobacco (aOR = 1.12, 95% CI 1.05, 1.21), cannabis (aOR = 1.11, 95% CI 1.04, 1.18), alcohol (aOR = 1.14, 95% CI 1.05, 1.24) and disordered eating risk (aOR = 2.28, 95% CI 2.13, 2.43). Analyses stratified by gender revealed cis-female students with OCD conditions were at increased risk for moderate/high risk alcohol (aOR = 1.18, 95% CI 1.08, 1.29), tobacco (aOR = 1.12, 95% CI 1.03, 1.22), cannabis (aOR = 1.13, 95% CI 1.06, 1.23) and disordered eating (aOR = 2.30, 9%% CI 2.14, 2.47). Among TGNC students, OCD conditions were associated with increased risk for moderate/high tobacco risk (aOR = 1.24, 95% CI 1.05, 1.48) and disordered eating (aOR = 2.14, 95% CI 1.85, 2.47). OCD conditions was only associated with disordered eating among male students (aOR = 2.34, 95% CI 1.93, 2.83). Discussion Young adult college students with OCD conditions exhibit a higher prevalence of medium/high risk alcohol, tobacco, and cannabis use and disordered eating compared to their counterparts without such conditions, even after adjusting for stress, depression, and anxiety.
Personalized tourism recommendation model based on temporal multilayer sequential neural network
Clinical outcomes of endocrine and other disorders induced by immune checkpoint inhibitors in Japanese patients
Development of colorimetric and fluorescent closed tube LAMP assay using simplified extraction for diagnosis of Meloidogyne enterolobii in root tissues
A multifunctional quasi-solid-state polymer electrolyte with highly selective ion highways for practical zinc ion batteries
Reduced ATP turnover during hibernation in relaxed skeletal muscle
Abstract Hibernating brown bears, due to a drastic reduction in metabolic rate, show only moderate muscle wasting. Here, we evaluate if ATPase activity of resting skeletal muscle myosin can contribute to this energy sparing. By analyzing single muscle fibers taken from the same bears, either during hibernation or in summer, we find that fibers from hibernating bears have a mild decline in force production and a significant reduction in ATPase activity. Single fiber proteomics, western blotting, and immunohistochemical analyses reveal major remodeling of the mitochondrial proteome during hibernation. Furthermore, using bioinformatical approaches and western blotting we find that phosphorylated myosin light chain, a known stimulator of basal myosin ATPase activity, is decreased in hibernating and disused muscles. These results suggest that skeletal muscle limits energy loss by reducing myosin ATPase activity, indicating a possible role for myosin ATPase activity modulation in multiple muscle wasting conditions.
“MoSpec”: A customized and integrated system for model development, verification and validation
Background and objective The growing availability of patient data from several clinical settings, fueled by advanced analysis systems and new diagnostics, presents a unique opportunity. These data can be used to understand disease progression and predict future outcomes. However, analysing this vast amount of data requires collaboration between physicians and experts from diverse fields like mathematics and engineering. Methods Mathematical models play a crucial role in interpreting patient data and enable in-silico simulations for diagnosis and treatment. To facilitate the creation and sharing of such models, the CNR-IASI BioMatLab group developed the “Gemini” (MoSpec/Autocoder) system, a framework allowing researchers with basic mathematical knowledge to quickly and correctly translate biological problems into Ordinary Differential Equations models. The system facilitates the development and computation of mathematical models for the interpretation of medical and biological phenomena, also using data from the clinical setting or laboratory experiments for parameter estimation. Results Gemini automatically generates code in multiple languages (C++, Matlab, R, and Julia) and automatically creates documentation, including code, figures, and visualizations. Conclusions This user-friendly approach promotes model sharing and collaboration among researchers, besides vastly increasing group productivity.
Bio particle swarm optimization and reinforcement learning algorithm for path planning of automated guided vehicles in dynamic industrial environments
AbstractAutomated guided vehicles play a crucial role in transportation and industrial environments. This paper presents a proposed Bio Particle Swarm Optimization (BPSO) algorithm for global path planning. The BPSO algorithm modifies the equation to update the particles’ velocity using the randomly generated angles, which enhances the algorithm’s searchability and avoids premature convergence. It is compared with Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Transit Search (TS) algorithms by benchmark functions. It has great performance in unimodal optimization problems, and it gains the best fitness value with fewer iterations and average runtime than other algorithms. The Q-learning method is implemented for local path planning to avoid moving obstacles and combines with the proposed BPSO for the safe operations of automated guided vehicles. The presented BPSO-RL algorithm combines the advantages of the swarm intelligence algorithm and the Q-learning method, which can generate the globally optimal path with fast computational speed and support in dealing with dynamic scenarios. It is validated through computational experiments with moving obstacles and compared with the PSO algorithm for AGV path planning.