A numerical investigation on active engine mounting systems and its optimization

In this paper, based on the previous research experiences in the lumped parameter modeling and study of active control mounts (ACM) model, an analytical model of active ACM in powertrain is developed and implemented in MATLAB. In order to validate this newly developed model in this work, a finite element analysis (FEA) method is conducted in ANSYS and the results of FEA is compared with analytical model for validation. After the validation, the control strategy is integrated into the analytical model by using the linear quadratic regulator (LQR) method. Numerical results show a good control performance. Furthermore, this work examines the application of genetic algorithms (GA) in optimizing the weight matrices of LQR. An optimal configuration is obtained and thus this approach could help the practical design of ACM systems

Multi-Grained Angle Representation for Remote Sensing Object Detection

Arbitrary-oriented object detection (AOOD) plays a significant role for image understanding in remote sensing scenarios. The existing AOOD methods face the challenges of ambiguity and high costs in angle representation. To this end, a multi-grained angle representation (MGAR) method, consisting of coarse-grained angle classification (CAC) and fine-grained angle regression (FAR), is proposed. Specifically, the designed CAC avoids the ambiguity of angle prediction by discrete angular encoding (DAE) and reduces complexity by coarsening the granularity of DAE. Based on CAC, FAR is developed to refine the angle prediction with much lower costs than narrowing the granularity of DAE. Furthermore, an Intersection over Union (IoU) aware FAR-Loss (IFL) is designed to improve accuracy of angle prediction using an adaptive re-weighting mechanism guided by IoU. Extensive experiments are performed on several public remote sensing datasets, which demonstrate the effectiveness of the proposed MGAR. Moreover, experiments on embedded devices demonstrate that the proposed MGAR is also friendly for lightweight deployments.Comment: 13 pages, 9 figures, 14 table

MiR-148a-3p suppresses the progression of gastric cancer cells through targeting ATP6AP2

Purpose: Gastric cancer (GC) is one of the most frequent tumors with high mortality rate, worldwide. A proper understanding of the mechanism  underlying its progression is required for its diagnosis and development of novel treatment option. MicroRNAs are associated with the development and advancement of different types of cancer, including GC. The current research was aimed at investigating the molecular and biological function of miR-148a-3p in GC development.Methods: A human normal gastric epithelial cell line, GES-1 (control) as well as four GC cell lines (NUGC-4, SNU-520, STKM-2 and MKN-74) were employed for the study. MiR-148a-3p and ATP6AP2 expression levels in GC cell lines were examined by RT-qPCR technique. Transfection procedure was used to upregulate miR-148a-3p expression in the MKN-45 cell line. MTT assay was utilized to evaluate cell viability in GC cell lines. The molecular interaction between miR-148a-3p and ATP6AP2 was predicted using bioinformatics system and the prediction was then validated by luciferase reporter assay.Results: Expression levels of miR-148-3p was low, whilst that of ATP6AP2 was high in GC cell lines. MiR-148a-3p overexpression resulted in the reduction of cell viability in GC cell lines. More so, it was confirmed that miR-148-3p, as a post-transcriptional regulator inhibited ATP6AP2 expression by having a negative association with it in GC cells. More so, ATP6AP2 was found to be a direct target of miR-148a-3p.Conclusion: Our results revealed that miR-148a-3p plays a crucial function in GC development through targeting ATP6AP2. This finding could be explored in the discovery of new therapeutic approaches for GC treatment. Keywords: ATP6AP2, Cell viability, Gastric cancer, miR-148a-3p, Progressio

Neighborhood Cognition Consistent Multi-Agent Reinforcement Learning

Social psychology and real experiences show that cognitive consistency plays an important role to keep human society in order: if people have a more consistent cognition about their environments, they are more likely to achieve better cooperation. Meanwhile, only cognitive consistency within a neighborhood matters because humans only interact directly with their neighbors. Inspired by these observations, we take the first step to introduce \emph{neighborhood cognitive consistency} (NCC) into multi-agent reinforcement learning (MARL). Our NCC design is quite general and can be easily combined with existing MARL methods. As examples, we propose neighborhood cognition consistent deep Q-learning and Actor-Critic to facilitate large-scale multi-agent cooperations. Extensive experiments on several challenging tasks (i.e., packet routing, wifi configuration, and Google football player control) justify the superior performance of our methods compared with state-of-the-art MARL approaches.Comment: Accepted by AAAI2020 with oral presentation (https://aaai.org/Conferences/AAAI-20/wp-content/uploads/2020/01/AAAI-20-Accepted-Paper-List.pdf). Since AAAI2020 has started, I have the right to distribute this paper on arXi

Whole Brain Mapping of Long-Range Direct Input to Glutamatergic and GABAergic Neurons in Motor Cortex

Long-range neuronal circuits play an important role in motor and sensory information processing. Determining direct synaptic inputs of excited and inhibited neurons is important for understanding the circuit mechanisms involved in regulating movement. Here, we used the monosynaptic rabies tracing technique, combined with fluorescent micro-optical sectional tomography, to characterize the brain-wide input to the motor cortex (MC). The whole brain dataset showed that the main excited and inhibited neurons in the MC received inputs from similar brain regions with a quantitative difference. With 3D reconstruction we found that the distribution of input neurons, that target the primary and secondary MC, had different patterns. In the cortex, the neurons projecting to the primary MC mainly distributed in the lateral and anterior portion, while those to the secondary MC distributed in the medial and posterior portion. The input neurons in the subcortical areas also showed the topographic shift model, as in the thalamus, the neurons distributed as outer and inner shells while the neurons in the claustrum and amygdala were in the ventral and dorsal part, respectively. These results lay the anatomical foundation to understanding the organized pattern of motor circuits and the functional differences between the primary and secondary MC

Successful transplantation of guinea pig gut microbiota in mice and its effect on pneumonic plague sensitivity

Microbiota-driven variations in the inflammatory response are predicted to regulate host responses to infection. Increasing evidence indicates that the gastrointestinal and respiratory tracts have an intimate relationship with each other. Gut microbiota can influence lung immunity whereby gut-derived injurious factors can reach the lungs and systemic circulation via the intestinal lymphatics. The intestinal microbiota’s ability to resist colonization can be extended to systemic infections or to pathogens infecting distant sites such as the lungs. Unlike the situation with large mammals, the microtus Yersinia pestis 201 strain exhibits strong virulence in mice, but nearly no virulence to large mammals (such as guinea pigs). Hence, to assess whether the intestinal microbiota from guinea pigs was able to affect the sensitivity of mice to challenge infection with the Y. pestis 201 strain, we fed mice with guinea pig diets for two months, after which they were administered 0.5 ml of guinea pig fecal suspension for 30 days by oral gavage. The stools from each mouse were collected on days 0, 15, and 30, DNA was extracted from them, and 16S rRNA sequencing was performed to assess the diversity and composition of the gut microbiota. We found that the intestinal microbiota transplants from the guinea pigs were able to colonize the mouse intestines. The mice were then infected with Yersinia pestis 201 by lung invasion, but no statistical difference was found in the survival rates of the mice that were colonized with the guinea pig’s gut microbiota and the control mice. This indicates that the intestinal microbiota transplantation from the guinea pigs did not affect the sensitivity of the mice to pneumonic plague

Pyrimido[4,5‐ d ]pyrimidin‐4(1 H )‐one Derivatives as Selective Inhibitors of EGFR Threonine 790 to Methionine 790 (T790M) Mutants

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/99681/1/8387_ftp.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/99681/2/anie_201302313_sm_miscellaneous_information.pd