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An examination of the effect of loneliness on the innovative behavior of health science faculty students

Chinese Medical Journal 2019年第2期132卷 171-182页

作者： Fadime Cinar Kerem Toker health Management Faculty of Health SciencesSabahattin Zaim UniversityIstanbul 34303Turkey health Management Faculty of Health SciencesBezmialem Vakif UniversityIstanbul 34050Turkey

Background:Contributing to the innovative behavior of individuals in the health management process is a desirable condition for increased health institution *** relationship between the sense of loneliness and individual innovation behaviors has not been studied and relevant literature is extremely *** purpose of this research was to examine the effect of an individual's sense of loneliness on their innovative ***:The research was performed between January and October *** effects of loneliness feelings on the individual innovative behaviors of 451 health science faculty students were *** data were collected using the "Individual Information Form," the "individual innovation scale," and the "University of California Los Angeles loneliness scale." The reliability and validity of the scales were tested with Structural Equation ***:It was found that the female participants showed exhibited more innovative behavior than the ***, there was no significant difference in the loneliness status of participants by gender.A group of 23-year-old individuals showed a significant difference in the risk taking dimension compared to other age ***-grade students had more points in the experimental openness and opinion leadership sub-dimension than the other *** was observed that the behavior is molded as the education level *** regression models showed that loneliness has a negative effect of -0.254 on experiential openness and the leadership of ideas, and has a negative effect of -0.216 on risk *** was no effect of the sub-dimensions of loneliness on change ***, on the individualistic behavior of physical loneliness, a -0.267 negative effect was *** loneliness has no effect on the sub-dimensions of individual ***, the total sense of loneliness was found to have a negative effect on total individual ***:The study result

关键词： Loneliness Innovative behavior health science

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Synergistic effect of bonding heterogeneity and phonon localization in introducing excellent thermoelectric properties in layered heteroanionic NdZnSbO material

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Journal of Energy Chemistry 2025年第1期100卷 259-272页

作者： Da Wan Shuwei Tang Shulin Bai Xiaodong Li Peng Ai Wanrong Guo Tuo Zheng College of Materials science and Engineering Liaoning Technical University faculty of Chemistry Northeast Normal University

Layered rare-earth metal oxides, harnessing the dual properties of oxides and two-dimensional layered materials, exhibit remarkable thermal stability and quantum confinement effects. Therefore, this work adopts the first-principles calculation combined with the Boltzmann transport theory to predict the thermoelectric properties of NdZnSbO compound. The coexistence of weak interlayer van der Waals interactions, robust intralayer ionic bonding, and partial covalent bonding leads to remarkable bonding heterogeneity, which engenders pronounced phonon scattering and imposes constraints on thermal transport along the out-of-plane direction. The weakened chemical bonds induced by the antibonding states, together with the rattling-like behavior of the Zn atom, culminate in the profound anharmonicity in the layered NdZnSbO compound. The weakening bond and heavy element contribute to the softness of phonon modes, which significantly diminishes the phonon group velocity. The redistribution-dominated four-phonon scattering process spans a large optical gap, which effectively reduces the lattice thermal conductivity. The NdZnSbO compound exhibits direct semiconductor characteristic with a bandgap of 0.73 e V by adopting the Heyd-Scuseria-Ernzerhof(HSE06) functional in combination with spin–orbit coupling(SOC) effect. The multi-valley feature of NdZnSbO compound augur favorably for band degeneracy, thus amplifying the power factor. Consequently, an optimal figure-of-merit(ZT) of 3.40 at 900 K is achieved for the n-type NdZnSbO compound. The present study delves deeply insights into the origins for the low thermal conductivity of NdZnSbO compound and proposes an optimization scheme to enhance overall thermoelectric performance.

关键词： Bond strength (chemical)

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Brain age estimation:premise,promise,and problems

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Neural Regeneration Research 2025年第8期20卷 2313-2314页

作者： Jarrad Perron Ji Hyun Ko Graduate Program in Biomedical Engineering Price Faculty of EngineeringUniversity of ManitobaWinnipegMBCanada PrairieNeuro Research Centre Kleysen Institute for Advanced MedicineHealth Sciences CentreWinnipegMBCanada Department of Human Anatomy and Cell science Rady Faculty of Health SciencesUniversity of ManitobaWinnipegMBCanada

Premise:The com bined effects of modern healthcare practices which prolong lifespan and declining birthrates have created unprecedented changes in age demographics worldwide that are especially pronounced in Japan,South Korea,Europe,and North *** old age is the most significant predictor of dementia,global healthcare systems must rise to the challenge of providing care for those with neurodegenerative disorders.

关键词： estimation providing birth

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Dynamic Multi-Graph Spatio-Temporal Graph Traffic Flow Prediction in Bangkok:An Application of a Continuous Convolutional Neural Network

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Computer Modeling in Engineering & sciences 2025年第1期142卷 579-607页

作者： Pongsakon Promsawat Weerapan Sae-dan Marisa Kaewsuwan Weerawat Sudsutad Aphirak Aphithana Department of Civil Engineering Faculty of EngineeringRamkhamkaeng UniversityBangkok10240Thailand Department of Computer Engineering Faculty of EngineeringRamkhamkaeng UniversityBangkok10240Thailand Department of Statistics Faculty of ScienceRamkhamkaeng UniversityBangkok10240Thailand

The ability to accurately predict urban traffic flows is crucial for optimising city ***,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mobility *** learning techniques,such as graph neural networks(GNNs),are popular for their ability to capture spatio-temporal ***,these models often become overly complex due to the large number of hyper-parameters *** this study,we introduce Dynamic Multi-Graph Spatial-Temporal Graph Neural Ordinary Differential Equation Networks(DMST-GNODE),a framework based on ordinary differential equations(ODEs)that autonomously discovers effective spatial-temporal graph neural network(STGNN)architectures for traffic prediction *** comparative analysis of DMST-GNODE and baseline models indicates that DMST-GNODE model demonstrates superior performance across multiple datasets,consistently achieving the lowest Root Mean Square Error(RMSE)and Mean Absolute Error(MAE)values,alongside the highest *** the BKK(Bangkok)dataset,it outperformed other models with an RMSE of 3.3165 and an accuracy of 0.9367 for a 20-min interval,maintaining this trend across 40 and 60 ***,on the PeMS08 dataset,DMST-GNODE achieved the best performance with an RMSE of 19.4863 and an accuracy of 0.9377 at 20 min,demonstrating its effectiveness over longer *** Los_Loop dataset results further emphasise this model’s advantage,with an RMSE of 3.3422 and an accuracy of 0.7643 at 20 min,consistently maintaining superiority across all time *** numerical highlights indicate that DMST-GNODE not only outperforms baseline models but also achieves higher accuracy and lower errors across different time intervals and datasets.

关键词： Graph neural networks convolutional neural network deep learning dynamic multi-graph spatio-temporal

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Navigating the pathways:TAR-DNA-binding-protein-43 aggregation,axonal transport,and local synthesis in amyotrophic lateral sclerosis pathology

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Neural Regeneration Research 2025年第10期20卷 2921-2922页

作者： Ori Bar Avi Eran Perlson Department of Physiology and Pharmacology Faculty of Medical&Health ScienceTel-Aviv UniversityTel-AvivIsrael Sagol School of Neuroscience Tel-Aviv UniversityTel-AvivIsrael

Neurons are highly polarized cells with axons reaching over a meter long in adult *** survive and maintain their proper function,neurons depend on specific mechanisms that regulate spatiotemporal signaling and metabolic events,which need to be carried out at the right place,time,and *** mechanisms include axonal transport,local synthesis,and liquid-liquid phase *** and malfunctions in these processes are correlated to neurodegenerative diseases such as amyotrophic lateral sclerosis(ALS).

关键词： synthesis local aggregation

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Photobiomodulation:a novel approach to promote trans-differentiation of adipose-derived stem cells into neuronal-like cells

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Neural Regeneration Research 2025年第2期20卷 598-608页

作者： Daniella Da Silva Madeleen Jansen van Rensburg Anine Crous Heidi Abrahamse Laser Research Centre Faculty of Health SciencesUniversity of JohannesburgDoornfonteinJohannesburgSouth Africa

Photobiomodulation,originally used red and near-infrared lasers,can alter cellular *** has been demonstrated that the visible spectrum at 451-540 nm does not necessarily increase cell proliferation,near-infrared light promotes adipose stem cell proliferation and affects adipose stem cell migration,which is necessary for the cells homing to the site of *** this in vitro study,we explored the potential of adipose-derived stem cells to differentiate into neurons for future translational regenerative treatments in neurodegenerative disorders and brain *** investigated the effects of various biological and chemical inducers on trans-differentiation and evaluated the impact of photobiomodulation using 825 nm near-infrared and 525 nm green laser light at 5 J/*** adipose-derived stem cells can be used in autologous grafting and photobiomodulation has been shown to have biostimulatory *** findings reveal that adipose-derived stem cells can indeed trans-differentiate into neuronal cells when exposed to inducers,with pre-induced cells exhibiting higher rates of proliferation and trans-differentiation compared with the control ***,green laser light stimulation led to notable morphological changes indicative of enhanced trans-differentiation,while near-infrared photobiomodulation notably increased the expression of neuronal *** biochemical analysis and enzyme-linked immunosorbent assays,we observed marked improvements in viability,proliferation,membrane permeability,and mitochondrial membrane potential,as well as increased protein levels of neuron-specific enolase and ciliary neurotrophic ***,our results demonstrate the efficacy of photobiomodulation in enhancing the trans-differentiation ability of adipose-derived stem cells,offering promising prospects for their use in regenerative medicine for neurodegenerative disorders and brain injuries.

关键词： differentiation inducers green photobiomodulation immortalized adipose-derived stem cell near-infrared photobiomodulation neurodegenerative disease neurogenesis photobiomodulation trans-differentiation

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A spotlight on dosage and subject selection for effective neuroprotection: exploring the central role of mitochondria

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Neural Regeneration Research 2025年第4期20卷 1081-1082页

作者： John Mitrofanis Jonathan Stone Michael R.Hamblin Pierre Magistretti Alim-Louis Benabid Glen Jeffery Fonds Clinatec UniversitéGrenoble AlpesGrenobleFrance School of Medical science University of SydneySydneyAustralia faculty of health sciences University of JohannesburgJohannesburgSouth Africa King Abdullah University of science and Technology ThuwalSaudi Arabia Institute of Ophthalmology University College LondonLondonUK

Neurons are notoriously vulnerable cell *** the slightest change in their internal and/or external environments will cause much distress and dysfunction,leading often to their death.A range of pathological conditions,including stroke,head trauma,and neurodegenerative disease,can generate stress in neurons,affecting their survival and proper *** most neural pathologies,mitochondria become dysfunctional and this plays a pivotal role in the process of cell *** challenge over the last few decades has been to develop effective interventions that improve neuronal homeostasis under pathological *** interventions,often referred to as disease-modifying or neuroprotective,have,however,proved frustratingly elusive,at both preclinical and,in particular,clinical *** this perspective,we highlight two factors that we feel are key to the development of effective neuroprotective *** are:firstly,the choice of dose of intervention and method of application,and secondly,the selection of subjects,whether they be patients or the animal model.

关键词： protective dosage distress

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Machine Learning Techniques in Predicting Hot Deformation Behavior of Metallic Materials

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Computer Modeling in Engineering & sciences 2025年第1期142卷 713-732页

作者： Petr Opela Josef Walek Jaromír Kopecek Department of Metallurgical Technologies Faculty of Materials Science and TechnologyVSB–Technical University of OstravaOstrava70800Czech Republic FZU—Institute of Physics of the Czech Academy of sciences Prague18200Czech Republic

In engineering practice,it is often necessary to determine functional relationships between dependent and independent *** relationships can be highly nonlinear,and classical regression approaches cannot always provide sufficiently reliable ***,Machine Learning(ML)techniques,which offer advanced regression tools to address complicated engineering issues,have been developed and widely *** study investigates the selected ML techniques to evaluate their suitability for application in the hot deformation behavior of metallic *** ML-based regression methods of Artificial Neural Networks(ANNs),Support Vector Machine(SVM),Decision Tree Regression(DTR),and Gaussian Process Regression(GPR)are applied to mathematically describe hot flow stress curve datasets acquired experimentally for a medium-carbon *** the GPR method has not been used for such a regression task before,the results showed that its performance is the most favorable and practically unrivaled;neither the ANN method nor the other studied ML techniques provide such precise results of the solved regression analysis.

关键词： Machine learning Gaussian process regression artificial neural networks support vector machine hot deformation behavior

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MARIE:One-Stage Object Detection Mechanism for Real-Time Identifying of Firearms

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Computer Modeling in Engineering & sciences 2025年第1期142卷 279-298页

作者： Diana Abi-Nader Hassan Harb Ali Jaber Ali Mansour Christophe Osswald Nour Mostafa Chamseddine Zaki Computer science Department Faculty of SciencesLebanese UniversityBeirut146404Lebanon College of Engineering and Technology American University of the Middle EastEgaila54200Kuwait Lab-STICC CNRS UMR 6285ENSTA-BretagneBrest29200France

Security and safety remain paramount concerns for both governments and individuals *** today’s context,the frequency of crimes and terrorist attacks is alarmingly increasing,becoming increasingly intolerable to ***,there is a pressing need for swift identification of potential threats to preemptively alert law enforcement and security forces,thereby preventing potential attacks or violent *** advancements in big data analytics and deep learning have significantly enhanced the capabilities of computer vision in object detection,particularly in identifying *** paper introduces a novel automatic firearm detection surveillance system,utilizing a one-stage detection approach named MARIE(Mechanism for Realtime Identification of Firearms).MARIE incorporates the Single Shot Multibox Detector(SSD)model,which has been specifically optimized to balance the speed-accuracy trade-off critical in firearm detection *** SSD model was further refined by integrating MobileNetV2 and InceptionV2 architectures for superior feature extraction *** experimental results demonstrate that this modified SSD configuration provides highly satisfactory performance,surpassing existing methods trained on the same dataset in terms of the critical speedaccuracy *** these innovations,MARIE sets a new standard in surveillance technology,offering a robust solution to enhance public safety effectively.

关键词： Firearm and gun detection single shot multi-box detector deep learning one-stage detector MobileNet inception convolutional neural network

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Translational challenges in amyotrophic lateral sclerosis therapy with macrophage migration inhibitory factor

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Neural Regeneration Research 2025年第9期20卷 2583-2584页

作者： Leenor Alfahel Aleksandar Rajkovic Adrian Israelson Department of Physiology and Cell Biology Faculty of Health SciencesBen-Gurion University of the NegevBeer ShevaIsraelThe School of Brain Sciences and CognitionBen-Gurion University of the NegevBeer ShevaIsrael

Macrophage migration inhibitory factor(MIF):MIF acts as a pleiotropic inflammatory mediator,playing regulatory roles in innate and adaptive immunity,neuroinflammation,neuroendocrine functions,and nervous system development(Matejuk et al.,2024).In recent years,MIF has attra cted significant inte rest from research groups as a potential target for the treatment of various neurodegenerative diseases,including Alzheimer's disease,Parkinson's disease,multiple sclerosis,and glioblastoma(Matejuk et al.,2024).

关键词： immunity sclerosis

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