Nodal Solutions for Some Second-Order Semipositone Integral Boundary Value Problems

Using bifurcation techniques, we first prove a global bifurcation theorem for nonlinear second-order semipositone integral boundary value problems. Then the existence and multiplicity of nodal solutions of the above problems are obtained. Finally, an example is worked out to illustrate our main results

Ergodic channel capacity of PPM-coded optical MIMO communications under combined effects

The ergodic channel capacity of wireless optical multiple-input multiple-output (MIMO) system with pulse position modulation (PPM) is investigated. The combined effects of atmospheric turbulence, atmospheric attenuation, pointing error and channel spatial correlation are taken into consideration. The expression of ergodic channel capacity is derived, and is further performed by Wilkinson approximation method for simplicity. The simulation results indicated that the strong spatial correlation has the greatest influence on the ergodic channel capacity, followed by pointing errors and atmospheric turbulence. Moreover, the ergodic channel capacity growth brought by space diversity only performs well under independent and weakly correlated channels. Properly increasing the size and spacing of the receiving apertures is an effective means of effectively increasing the ergodic channel capacity

Neurotrophic basis to the pathogenesis of depression and phytotherapy

Depression is a major neuropsychiatric disease that considerably impacts individuals’ psychosocial function and life quality. Neurotrophic factors are now connected to the pathogenesis of depression, while the definitive neurotrophic basis remains elusive. Besides, phytotherapy is alternative to conventional antidepressants that may minimize undesirable adverse reactions. Thus, further research into the interaction between neurotrophic factors and depression and phytochemicals that repair neurotrophic factors deficit is highly required. This review highlighted the implication of neurotrophic factors in depression, with a focus on the brain-derived neurotrophic factor (BDNF), glial cell line-derived neurotrophic factor (GDNF), vascular endothelial growth factor (VEGF), and nerve growth factor (NGF), and detailed the antidepressant activities of various phytochemicals targeting neurotrophic factors. Additionally, we presented future opportunities for novel diagnostic and therapeutic strategies for depression and provided solutions to challenges in this area to accelerate the clinical translation of neurotrophic factors for the treatment of depression

Relationship between Extraversion and Employees’ Innovative Behavior and Moderating Effect of Organizational Innovative Climate

This paper aims to clarify the relationship between extraversion and employees’ innovative and disclose the moderating effect of organizational innovative climate on that relationship. To this end, 300 employees were selected from various enterprises in three Chinese cities, and subjected to a questionnaire survey based on the five factor model (FFM) and 5-point Likert scale. Through statistical regressions, the author explored the effects of extraversion and organizational innovative climate have on employees’ innovative behavior. Then, the organizational innovative climate was divided into five dimensions, and the feature activation theory was implemented to reveal the moderating effect of each dimension on relationship between extraversion and employees’ innovation. Through the above analysis, it is concluded that extraversion has a positive effect on employees’ innovative behavior; the five dimensions of organizational innovative climate all exert a positive effect on employees’ innovative behavior; the resource support in organizational innovative climate has a moderating effect on the relationship between extraversion and employees’ innovation. The research findings shed new light on the improvement of organizational innovative and the construction of an innovative country

Transfer Learning Applied to Stellar Light Curve Classification

Variability carries physical patterns and astronomical information of objects, and stellar light curve variations are essential to understand the stellar formation and evolution processes. The studies of variations in stellar photometry have the potential to expand the list of known stars, protostars, binary stars, and compact objects, which could shed more light on stages of stellar lifecycles. The progress in machine-learning techniques and applications has developed modern algorithms to detect and condense features from big data, which enables us to classify stellar light curves efficiently and effectively. We explore several deep-learning methods on variable star classifications. The sample of light curves is constructed with $\delta$ Scuti, $\gamma$ Doradus, RR Lyrae, eclipsing binaries, and hybrid variables from \textit{Kepler} observations. Several algorithms are applied to transform the light curves into images, continuous wavelet transform (CWT), Gramian angular fields, and recurrent plots. We also explore the representation ability of these algorithms. The processed images are fed to several deep-learning methods for image recognition, including VGG-19, GoogLeNet, Inception-v3, ResNet, SqueezeNet, and Xception architectures. The best transformation method is CWT, resulting in an average accuracy of 95.6\%. VGG-19 shows the highest average accuracy of 93.25\% among all architectures, while it shows the highest accuracy of 97.2\% under CWT transformation method. The prediction can reach $\sim1000$ light curves per second by using NVIDIA RTX 3090. Our results indicate that the combination of big data and deep learning opens a new path to classify light curves automatically.Comment: 30 pages, 19 figure

Transmembrane routes of cationic liposome-mediated gene delivery using human throat epidermis cancer cells

For studying the mechanism of cationic liposome-mediated transmembrane routes for gene delivery, various inhibitors of endocytosis were used to treat human throat epidermis cancer cells, Hep-2, before transfection with Lipofectamine 2000/pGFP-N2 or Lipofectamine 2000/pGL3. To eliminate the effect of inhibitor toxicity on transfection, the RLU/survival rate was used to represent the transfection efficiency. Chlorpromazine and wortmannin, clathrin inhibitors, decreased transfection efficiency by 44 % (100 μM) and 31 % (100 nM), respectively. At the same time, genistein, a caveolin inhibitor, decreased it by 30 % (200 μM). Thus combined transmembrane routes through the clathrin and caveolae-mediated pathways were major mechanisms of cell uptake for the cationic liposome-mediated gene delivery. After entering the cells, microtubules played an important role on gene delivery as vinblastine, a microtubulin inhibitor, could reduce transfection efficiency by 41 % (200 nM)