Meta-Reinforcement Learning for Timely and Energy-efficient Data Collection in Solar-powered UAV-assisted IoT Networks

Unmanned aerial vehicles (UAVs) have the potential to greatly aid Internet of Things (IoT) networks in mission-critical data collection, thanks to their flexibility and cost-effectiveness. However, challenges arise due to the UAV's limited onboard energy and the unpredictable status updates from sensor nodes (SNs), which impact the freshness of collected data. In this paper, we investigate the energy-efficient and timely data collection in IoT networks through the use of a solar-powered UAV. Each SN generates status updates at stochastic intervals, while the UAV collects and subsequently transmits these status updates to a central data center. Furthermore, the UAV harnesses solar energy from the environment to maintain its energy level above a predetermined threshold. To minimize both the average age of information (AoI) for SNs and the energy consumption of the UAV, we jointly optimize the UAV trajectory, SN scheduling, and offloading strategy. Then, we formulate this problem as a Markov decision process (MDP) and propose a meta-reinforcement learning algorithm to enhance the generalization capability. Specifically, the compound-action deep reinforcement learning (CADRL) algorithm is proposed to handle the discrete decisions related to SN scheduling and the UAV's offloading policy, as well as the continuous control of UAV flight. Moreover, we incorporate meta-learning into CADRL to improve the adaptability of the learned policy to new tasks. To validate the effectiveness of our proposed algorithms, we conduct extensive simulations and demonstrate their superiority over other baseline algorithms

Analysis of geological hazards caused by the “23 • 7” heavy rainfall in the northern section of Taihang Mountain in Hebei Province

Heavy rainfall is the main factor triggering geological disasters. In the northern region of China, most of the researches focus on the geologic disasters caused by short-term heavy rainfall, and the researches on the characteristics of geologic disasters under regional extreme precipitation conditions are still insufficient. Based on the sample analysis of geological disasters triggered by the “23•7” heavy rainfall, the regular characteristics of geological disasters in the Hebei section of the Taihang Mountains were studied. The results show that: (1) geologic hazards show the trend of multiple and group occurrence, and the number of occurrences reaches a new high in history, and the types of avalanches, landslides, and mudslides are the main ones, which stimulate new geologic hazards to increase significantly; (2) the spatial and temporal scales of occurrence of geologic hazards and the area of heavy rainfall are highly coincident with each other, and the south and north sections of the Taihang Mountains show a differentiated distribution; (3) mudslides cause the most damage, and slope-type mudslides are obviously more frequent, and the loose material-covered landslides are more frequent and easier to occur. cover type landslides are more frequent and prone to occur. The results of the study can provide a reference for the prevention of geologic disasters under extreme precipitation conditions

FDXR drives primary and endocrine-resistant tumor cell growth in ER+ breast cancer via CPT1A-mediated fatty acid oxidation

Background The majority of breast cancers (BCs) expressing estrogen receptor (ER) have shown endocrine resistance. Our previous study demonstrated that ferredoxin reductase (FDXR) promoted mitochondrial function and ER+ breast tumorigenesis. But the underlying mechanism is not clear. Methods Liquid chromatography (LC) tandem mass spectrometry (MS/MS)-based metabolite profiling was utilized to reveal the metabolites regulated by FDXR. RNA microarray was utilized to determine the potential downstream targets of FDXR. Seahorse XF24 analyzer was performed to analyze the FAO-mediated oxygen consumption rate (OCR). Q-PCR and western blotting assays were used to measure expression levels of FDXR and CPT1A. MTS, 2D colony formation and anchorage-independent growth assays were used to evaluate the effects of FDXR or drug treatments on tumor cell growth of primary or endocrine-resistant breast cancer cells. Results We found that depletion of FDXR inhibited fatty acid oxidation (FAO) by suppressing CPT1A expression. Endocrine treatment increased the expression levels of both FDXR and CPT1A. Further, we showed that depletion of FDXR or FAO inhibitor etomoxir treatment reduced primary and endocrine-resistant breast cancer cell growth. Therapeutically, combining endocrine therapy with FAO inhibitor etomoxir synergistically inhibits primary and endocrine-resistant breast cancer cell growth. Discussion We reveal that the FDXR-CPT1A-FAO signaling axis is essential for primary and endocrine-resistant breast cancer cell growth, thus providing a potential combinatory therapy against endocrine resistance in ER+ breast cancer

FDXR drives primary and endocrine-resistant tumor cell growth in ER+ breast cancer via CPT1A-mediated fatty acid oxidation

BackgroundThe majority of breast cancers (BCs) expressing estrogen receptor (ER) have shown endocrine resistance. Our previous study demonstrated that ferredoxin reductase (FDXR) promoted mitochondrial function and ER+ breast tumorigenesis. But the underlying mechanism is not clear.MethodsLiquid chromatography (LC) tandem mass spectrometry (MS/MS)-based metabolite profiling was utilized to reveal the metabolites regulated by FDXR. RNA microarray was utilized to determine the potential downstream targets of FDXR. Seahorse XF24 analyzer was performed to analyze the FAO-mediated oxygen consumption rate (OCR). Q-PCR and western blotting assays were used to measure expression levels of FDXR and CPT1A. MTS, 2D colony formation and anchorage-independent growth assays were used to evaluate the effects of FDXR or drug treatments on tumor cell growth of primary or endocrine-resistant breast cancer cells.ResultsWe found that depletion of FDXR inhibited fatty acid oxidation (FAO) by suppressing CPT1A expression. Endocrine treatment increased the expression levels of both FDXR and CPT1A. Further, we showed that depletion of FDXR or FAO inhibitor etomoxir treatment reduced primary and endocrine-resistant breast cancer cell growth. Therapeutically, combining endocrine therapy with FAO inhibitor etomoxir synergistically inhibits primary and endocrine-resistant breast cancer cell growth.DiscussionWe reveal that the FDXR-CPT1A-FAO signaling axis is essential for primary and endocrine-resistant breast cancer cell growth, thus providing a potential combinatory therapy against endocrine resistance in ER+ breast cancer

Timetable coordination of first trains in urban railway network: A case study of Beijing

A model of timetable coordination of first trains in urban railway networks, based on the importance of lines and transfer stations, is proposed in this paper. A sub-network connection method is developed, and a mathematical programming solver is utilized to solve the suggested model. A simple test network and a real network of Beijing urban railway network are modeled to verify the effectiveness of our suggested model. Results demonstrate that the proposed model is effective in improving the transfer performance in that they reduce the connection time significantly

Molecular epidemiology of measles viruses in China, 1995–2003

This report describes the genetic characterization of 297 wild-type measles viruses that were isolated in 24 provinces of China between 1995 and 2003. Phylogenetic analysis of the N gene sequences showed that all of the isolates belonged to genotype H1 except 3 isolates, which were genotype A. The nucleotide sequence and predicted amino acid homologies of the 294-genotype H1 strains were 94.7%–100% and 93.3%–100%, respectively. The genotype H1 isolates were divided into 2 clusters, which differed by approximately 2.9% at the nucleotide level. Viruses from both clusters were distributed throughout China with no apparent geographic restriction and multiple co-circulating lineages were present in many provinces. Even though other measles genotypes have been detected in countries that border China, this report shows that genotype H1 is widely distributed throughout the country and that China has a single, endemic genotype. This important baseline data will help to monitor the progress of measles control in China

Designing robust schedule coordination scheme for transit networks with safety control margins

We propose a robust schedule coordination scheme which combines timetable planning with a semi-flexible departure delayed control strategy in case of disruptions. The flexibility is provided by allowing holding for the late incoming bus within a safety control margin (SCM). In this way, the stochastic travel time is addressed by the integration of real-time control and slacks at the planning phase. The schedule coordination problem then jointly optimises the planning headways and slack times in the timetable subject to SCM. Analytical formulations of cost functions are derived for three types of operating modes: uncoordinated operation, departure punctual control and departure delayed control. The problem is formulated as a stochastic mixed integer programming model and solved by a branch-and-bound algorithm. Numerical results provide an insight into the interaction between SCM and slack times, and demonstrate that the proposed model leads to cost saving and higher efficiency when SCM is considered. Compared to the conventional operating modes, the proposed method also presents advantages in transfer reliability and robustness to delay and demand variation