The Almost Sure Asymptotic Stability and Boundedness of Stochastic Functional Differential Equations with Polynomial Growth Condition

Stability and boundedness are two of the most important topics in the study of stochastic functional differential equations (SFDEs). This paper mainly discusses the almost sure asymptotic stability and the boundedness of nonlinear SFDEs satisfying the local Lipschitz condition but not the linear growth condition. Here we assume that the coefficients of SFDEs are polynomial or dominated by polynomial functions. We give sufficient criteria on the almost sure asymptotic stability and the boundedness for this kind of nonlinear SFDEs. Some nontrivial examples are provided to illustrate our results

Asymptotic stability and boundedness of stochastic functional differential equations with Markovian switching

This paper is concerned with the boundedness, exponential stability and almost sure asymptotic stability of stochastic functional differential equations (SFDEs) with Markovian switching. The key technique used is the method of multiple Lyapunov functions. We use two auxiliary functions to dominate the corresponding different Lyapunov function in different mode while the diffusion operator in different model is controlled by other multiple auxiliary functions. Our conditions on the diffusion operator are weaker than those in the related existing works

Deep learning in remote sensing: a review

Standing at the paradigm shift towards data-intensive science, machine learning techniques are becoming increasingly important. In particular, as a major breakthrough in the field, deep learning has proven as an extremely powerful tool in many fields. Shall we embrace deep learning as the key to all? Or, should we resist a 'black-box' solution? There are controversial opinions in the remote sensing community. In this article, we analyze the challenges of using deep learning for remote sensing data analysis, review the recent advances, and provide resources to make deep learning in remote sensing ridiculously simple to start with. More importantly, we advocate remote sensing scientists to bring their expertise into deep learning, and use it as an implicit general model to tackle unprecedented large-scale influential challenges, such as climate change and urbanization.Comment: Accepted for publication IEEE Geoscience and Remote Sensing Magazin

Case report: Minimally invasive removal of a dislodged thoracoamniotic shunt with an integral cystoscope in a preterm infant

IntroductionFetal pleural effusion is a rare condition that is associated with significant mortality. Although the insertion of fetal thoracoamniotic shunts can improve perinatal outcomes, there are several associated complications, such as intrathoracic dislodgement of the shunts. The optimal neonatal treatment for retained shunts remains uncertain.Case DescriptionA male infant was born at 32 weeks of gestation. He had antenatal hydrothorax that was detected at 27 weeks of gestation and was managed by intrauterine thoracoamniotic shunting. However, the shunt catheter dislodged into the fetal chest, which caused reaccumulated pleural effusion and respiratory distress requiring ventilatory support after birth. After the patient’s condition stabilized, minimally invasive removal of the retained catheter was performed on day 17 of life using an integral pediatric cystoscope via a 3-mm thoracic incision. The procedure took approximately 5 min. The postoperative course was uneventful, and the patient, who was discharged 39 days postnatally, is thriving at the 6-month follow-up.ConclusionsWe present a novel and effective approach to the management of an intrathoracic shunt using an integral cystoscope. This approach may offer a valuable alternative to traditional thoracoscopy in the neonatal period

Customizing the promotion strategies of integrated air-bus service based on passenger satisfaction

The integrated air-bus service expands the catchment area and alleviates congestion of regional airports. To gain further insights into the unexplored potential attributes of the integrated service that generate passenger satisfaction, this paper utilizes a two-stage analysis approach to identify the key promotion factors for passengers from different constituents. Based on the survey data collected in Nanjing Lukou International Airport, this paper 1) uses k-means clustering to categorize respondents into four groups. 2) Combines the gradient boosting decision tree and impact asymmetry analysis to identify the attributes that have nonlinear influences on the overall service satisfaction for each group respectively. Results suggest that the timetable of the airport bus is critical for all passenger groups. Interestingly, there are noticeable differences in passenger satisfaction with the accessibility, cost affordability, comfort, reliability, and integration of the integrated service, providing the basis for customizing service promotion strategies among different passenger groups and airports.</p

Life cycle assessment shows that retrofitting coal-fired power plants with fuel cells will substantially reduce greenhouse gas emissions

Addressing emissions released from coal-fired power plants (CFPPs) is vital to mitigate climate change. China aims to replace 240 TWh CFPPs with fuel cell (FC) technologies by 2050 to achieve carbon-neutrality goals. However, FCs are not emission-free throughout their technology life cycle, and FC effectiveness will vary depending on the CFPP configuration. Despite these uncertainties, a comprehensive evaluation of on-site CFPP-to-FC mitigation potential throughout the entire life cycle remains underexplored. Here, we use a prospective life cycle assessment to evaluate the inclusive mitigation potential of retrofitting 240 TWh CFPPs via four FCs that use wind power/natural gas as feedstocks. We find CO2, PM2.5, and SO2 emissions decrease by 72.0%–97.0%, 55.5%–92.6%, and 23.1%–86.1%, respectively, by 2050. Wind-electrolysis hydrogen FCs enable the largest life cycle CO2 reduction, but mining metals for wind turbines reduces PM2.5 and SO2 savings. Prioritizing FC deployment in northern China could double the mitigation potential. Our study provides insights for designing carbon-neutrality CFPP-to-FC roadmaps in China

Identification of significant loci for drought resistance and root traits at seedling stage with a set of maize introgression lines

Genetic dissection of the genetic basis of drought resistance is important for crop improvement. In this study, significant loci for drought resistance related traits at seedling stage were identified with a set of maize introgression lines under two environments. Two drought resistance indicators, leaf-drying degree under medium drought stress (LDM) and severe drought stress (LDS), and three root traits, root dry weight under drought stress (RWS), root length under drought stress (RLS), and root number under drought stress (RNS) were investigated. A total of 31 and 25 significant loci for LDM and LDS were identified, respectively, and 20 of them were commonly detected under both environments. For the three root traits, 41 significant loci were detected with 20 loci identified under both environments. Of the 97 significant loci, only 19 loci related to both leaf-drying degree and root traits under stress simultaneously, suggesting that these root traits had limited contribution to drought resistance at seedling stage. The significant loci detected in this study would be useful in molecular breeding for drought resistance in maize

Chronic oleoylethanolamide treatment attenuates diabetes-induced mice encephalopathy by triggering peroxisome proliferator-activated receptor alpha in the hippocampus.

Brain is a site of diabetic end-organ damage. Diabetes-associated cognitive dysfunction, referred as "diabetic encephalopathy" (DE) has been coined for the patients with type 2 diabetes mellitus showing decline in their cognitive function, especially weak episodic memory, cognitive inflexibility and poor psychomotor performance leading towards Alzheimer’s disease. Current evidence supported that aberrant synapses, energy metabolism imbalance, advanced glycation end products (AGEs) accumulation and Tau hyperphosphorylation are associated with cognition deficits induced by diabetes. Oleoylethanolamide (OEA), an endogenous peroxisome proliferator-activated receptor alpha (PPARα) agonist, has anti-hyperlipidemia, anti-inflammatory and neuroprotective activities. However, the effect of OEA on DE is unknown. Therefore, we tested its influence against cognitive dysfunction in high fat diet and streptozotocin (HFD + STZ)-induced diabetic C57BL/6J and PPARα--/- mice using Morris water maze (MWM) test. Neuron staining, dementia markers and neuroplasticity in the hippocampus were assessed to evaluate the neuropathological changes. The results showed that chronic OEA treatment significantly lowered hyperglycemia, recovered cognitive performance, reduced dementia markers, and inhibited hippocampal neuron loss and neuroplasticity impairments in diabetic mice. In contrast, the changes in MWM performance and neuron loss were not observed in PPARα knockout mice via OEA administration. These results indicated that OEA may provide a potential alternative therapeutic for DE by activating PPARα signaling