The Development of Militant Organizations’ Print Media in Pakistan

The militant organizations’ print media in Pakistan also could be called jihad media, new media or radical media. Different from the mainstream media in Pakistan, the media of militant organizations were one of the alternative media. The media of militant organizations originated in 1979, since the outset of the war between Soviet Union and Afghanistan. The media of militant organizations’ rise had deep ideological roots. And the media of militant organizations were influenced by social environment in Pakistan at that time. This paper was focused on the rising and preliminary developments of the militant organizations’ print media in Pakistan. The militant organizations’ print media in Pakistan were closely related in Pakistani media situation. Terrorist activities were now rampant around the world. So, it had great practical significance to study the history and operation of the militant organizations’ print media

The Weighted Support Vector Machine Based on Hybrid Swarm Intelligence Optimization for Icing Prediction of Transmission Line

Not only can the icing coat on transmission line cause the electrical fault of gap discharge and icing flashover but also it will lead to the mechanical failure of tower, conductor, insulators, and others. It will bring great harm to the people’s daily life and work. Thus, accurate prediction of ice thickness has important significance for power department to control the ice disaster effectively. Based on the analysis of standard support vector machine, this paper presents a weighted support vector machine regression model based on the similarity (WSVR). According to the different importance of samples, this paper introduces the weighted support vector machine and optimizes its parameters by hybrid swarm intelligence optimization algorithm with the particle swarm and ant colony (PSO-ACO), which improves the generalization ability of the model. In the case study, the actual data of ice thickness and climate in a certain area of Hunan province have been used to predict the icing thickness of the area, which verifies the validity and applicability of this proposed method. The predicted results show that the intelligent model proposed in this paper has higher precision and stronger generalization ability

A model-driven deep reinforcement learning heuristic algorithm for resource allocation in ultra-dense cellular networks

Resource allocation in ultra dense network (UDN) is an multi-objective optimization problem since it has to consider the tradeoff among spectrum efficiency (SE), energy efficiency (EE) and fairness. The existing methods can not effectively solve this NP-hard nonconvex problem, especially in the presence of limited channel state information (CSI). In this paper, we investigate a novel model-driven deep reinforcement learning assisted resource allocation method. We first design a novel deep neural network (DNN)-based optimization framework consisting of a series of Alternating Direction Method of Multipliers (ADMM) iterative procedures, which makes the CSI as the learned weights. Then a novel channel information absent Q-learning resource allocation (CIAQ) algorithm is proposed to train the DNN-based optimization framework without massive labeling data, where the SE, the EE, and the fairness can be jointly optimized by adjusting discount factor. Our simulation results show that, the proposed CIAQ with rapid convergence speed not only well characterizes the extent of optimization objective with partial CSI, but also significantly outperforms the current random initialization method of neural network and the other existing resource allocation algorithms in term of the tradeoff among the SE, EE and fairness

Cathepsins in oral diseases: mechanisms and therapeutic implications

Cathepsins are a type of lysosomal globulin hydrolase and are crucial for many physiological processes, including the resorption of bone matrix, innate immunity, apoptosis, proliferation, metastasis, autophagy, and angiogenesis. Findings regarding their functions in human physiological processes and disorders have drawn extensive attention. In this review, we will focus on the relationship between cathepsins and oral diseases. We highlight the structural and functional properties of cathepsins related to oral diseases, as well as the regulatory mechanisms in tissue and cells and their therapeutic uses. Elucidating the associated mechanism between cathepsins and oral diseases is thought to be a promising strategy for the treatment of oral diseases and may be a starting point for further studies at the molecular level

Anthropogenic impact on diazotrophic diversity in the mangrove rhizosphere revealed by nifH pyrosequencing

Diazotrophs in the mangrove rhizosphere play a major role in providing new nitrogen to the mangrove ecosystem and their composition and activity are strongly influenced by anthropogenic activity and ecological conditions. In this study, the diversity of the diazotroph communities in the rhizosphere sediment of five tropical mangrove sites with different levels of pollution along the north and south coastline of Singapore were studied by pyrosequencing of the nifH gene. Bioinformatics analysis revealed that in all the studied locations, the diazotroph communities comprised mainly of members of the diazotrophic cluster I and cluster III. The detected cluster III diazotrophs, which were composed entirely of sulfate-reducing bacteria, were more abundant in the less polluted locations. The metabolic capacities of these diazotrophs indicate the potential for bioremediation and resiliency of the ecosystem to anthropogenic impact. In heavily polluted locations, the diazotrophic community structures were markedly different and the diversity of species was significantly reduced when compared with those in a pristine location. This, together with the increased abundance of Marinobacterium, which is a bioindicator of pollution, suggests that anthropogenic activity has a negative impact on the genetic diversity of diazotrophs in the mangrove rhizosphere

hCeO2@ Cu5.4O nanoparticle alleviates inflammatory responses by regulating the CTSB–NLRP3 signaling pathway

Inflammatory responses, especially chronic inflammation, are closely associated with many systemic diseases. There are many ways to treat and alleviate inflammation, but how to solve this problem at the molecular level has always been a hot topic in research. The use of nanoparticles (NPs) as anti-inflammatory agents is a potential treatment method. We synthesized new hollow cerium oxide nanomaterials (hCeO2 NPs) doped with different concentrations of Cu5.4O NPs [the molar ratio of Cu/(Ce + Cu) was 50%, 67%, and 83%, respectively], characterized their surface morphology and physicochemical properties, and screened the safe concentration of [email protected] using the CCK8 method. Macrophages were cultured, and P.g-lipopolysaccharide-stimulated was used as a model of inflammation and co-cultured with [email protected] NPs. We then observe the effect of the transcription levels of CTSB, NLRP3, caspase-1, ASC, IL-18, and IL-1β by PCR and detect its effect on the expression level of CTSB protein by Western blot. The levels of IL-18 and IL-1β in the cell supernatant were measured by enzyme-linked immunosorbent assay. Our results indicated that [email protected] NPs could reduce the production of reactive oxygen species and inhibit CTSB and NLRP3 to alleviate the damage caused by the inflammatory response to cells. More importantly, [email protected] NPs showed stronger anti-inflammatory effects as Cu5.4O NP doping increased. Therefore, the development of the novel nanomaterial [email protected] NPs provides a possible new approach for the treatment of inflammatory diseases