Trajectory Optimization and NMPC Tracking for a Fixed Wing UAV in Deep Stall with Perch Landing

This paper presents a novel recovery technique for a fixed-wing UAV (Unmanned Aerial Vehicle) based on constrained optimization: i) we propose a trajectory generation for landing the UAV where it first reduces its altitude by deep stalling, then perches on a recovery net, ii) we design an NMPC (Nonlinear Model Predictive Control) tracking controller with terminal constraints for the optimal generated trajectory under disturbances. Compared to nominal net recovery procedures, this technique greatly reduces the landing time and the final airspeed of the UAV. Simulation results for various wind conditions demonstrate the feasibility of the idea.Comment: 8 pages, 13 figure

Memory Usage Inference for Object-Oriented Programs

We present a type-based approach to statically derive symbolic closed-form formulae that characterize the bounds of heap memory usages of programs written in object-oriented languages. Given a program with size and alias annotations, our inference system will compute the amount of memory required by the methods to execute successfully as well as the amount of memory released when methods return. The obtained analysis results are useful for networked devices with limited computational resources as well as embedded software.Singapore-MIT Alliance (SMA

Helminth eggs die-off and nutrients : human excreta storage experiment

Are the current practices of handling human excreta for agricultural purposes by farmers in Vietnam good enough?This study set up an excreta storage experiment to research how to inactivate Ascaris lumbricoides eggs and stillmaintain the nutrient value of human excreta

A novel segmentation framework for uveal melanoma in magnetic resonance imaging based on class activation maps

An automatic and accurate eye tumor segmentation from Magnetic Resonance images (MRI) could have a great clinical contribution for the purpose of diagnosis and treatment planning of intra-ocular cancer. For instance, the characterization of uveal melanoma (UM) tumors would allow the integration of 3D information for the radiotherapy and would also support further radiomics studies. In this work, we tackle two major challenges of UM segmentation: 1) the high heterogeneity of tumor characterization in respect to location, size and appearance and, 2) the difficulty in obtaining ground-truth delineations of medical experts for training. We propose a thorough segmentation pipeline consisting of a combination of two Convolutional Neural Networks (CNN). First, we consider the class activation maps (CAM) output from a Resnet classification model and the combination of Dense Conditional Random Field (CRF) with a prior information of sclera and lens from an Active Shape Model (ASM) to automatically extract the tumor location for all MRIs. Then, these immediate results will be inputted into a 2D-Unet CNN whereby using four encoder and decoder layers to produce the tumor segmentation. A clinical data set of 1.5T T1-w and T2-w images of 28 healthy eyes and 24 UM patients is used for validation. We show experimentally in two different MRI sequences that our weakly 2D-Unet approach outperforms previous state-of-the-art methods for tumor segmentation and that it achieves equivalent accuracy as when manual labels are used for training. These results are promising for further large-scale analysis and for introducing 3D ocular tumor information in the therapy planning

Flexural-strengthening efficiency of cfrp sheets for unbonded post-tensioned concrete T-beams

There has been a limited number of studies about the flexural behavior of unbonded post-tensioned concrete (UPC) beams strengthened with carbon fibre reinforced polymer (CFRP) and these studies have not systematically examined the effect of CFRP sheets on the tendon strain as well as the strengthening efficiency. Moreover, current design guides for the FRP strengthening techniques have not provided any design procedure for UPC structures. This study, thus, investigates the influence of CFRP sheet ratio on the flexural behavior of CFRP-strengthened UPC T-beams and quantifies its effect upon tendon behavior in this kind of UPC beams. The testing program consisted of nine large-scale UPC T-beams strengthened by different layers of CFRP sheets with or without CFRP U-wrapped anchors. The experimental results have shown that the use of CFRP sheets and CFRP U-wrapped anchors significantly affected the tendon strain. The FRP reinforcement ratio governed the flexural capacity, the crack width, the mid-span displacement, and the ductility of the beams in which the strengthening efficiency reduces with the increased number of CFRP layers. The configuration of the CFRP U-wrapped anchors affected the strain of the CFRP sheets, the failure mode and thus the beam behavior. In addition, semi-empirical equations were proposed to estimate the actual strain of unbonded tendons in which the effect of the CFRP sheets and CFRP U-wrapped anchors have been taken into consideration. The proposed equations, which are simple to use, yield reliable predictions with a small variation

Feasibility of wearable monitors to detect heart rate variability in children with hand, foot and mouth disease

Hand foot and mouth disease (HFMD) is caused by a variety of enteroviruses, and occurs in large outbreaks in which a small proportion of children deteriorate rapidly with cardiopulmonary failure. Determining which children are likely to deteriorate is difficult and health systems may become overloaded during outbreaks as many children require hospitalization for monitoring. Heart rate variability (HRV) may help distinguish those with more severe diseases but requires simple scalable methods to collect ECG data.We carried out a prospective observational study to examine the feasibility of using wearable devices to measure HRV in 142 children admitted with HFMD at a children's hospital in Vietnam. ECG data were collected in all children. HRV indices calculated were lower in those with enterovirus A71 associated HFMD compared to those with other viral pathogens.HRV analysis collected from wearable devices is feasible in a low and middle income country (LMIC) and may help classify disease severity in HFMD

Tridimensional few-layer graphene-like structures from sugar-salt mixtures as high-performance supercapacitor electrodes

© 2018 Elsevier Ltd This work describes a straightforward approach to the production of highly-performing and cost-effective C-based materials for energy storage application while proposing an original and effective method to the control of the final material morphology. Indeed, robust few-layer graphene-like and highly open-cell structures have been prepared by a modified chemical activation procedure starting from costless sugar/salt mixtures. The as-prepared C-samples ensure high ion-accessible surface area and low ion transport resistance, two key features for the fabrication of effective electrochemical double layer supercapacitors. A selected sample from this series exhibits high specific capacitance (Cg) (312 and 234 F g−1 at 0.5 and 50 A g−1, respectively, in 0.5 M H2SO4), particularly at high current density values, along with excellent cycling stability and Cg retention for increasing charge–discharge rates

TextANIMAR: Text-based 3D Animal Fine-Grained Retrieval

3D object retrieval is an important yet challenging task, which has drawn more and more attention in recent years. While existing approaches have made strides in addressing this issue, they are often limited to restricted settings such as image and sketch queries, which are often unfriendly interactions for common users. In order to overcome these limitations, this paper presents a novel SHREC challenge track focusing on text-based fine-grained retrieval of 3D animal models. Unlike previous SHREC challenge tracks, the proposed task is considerably more challenging, requiring participants to develop innovative approaches to tackle the problem of text-based retrieval. Despite the increased difficulty, we believe that this task has the potential to drive useful applications in practice and facilitate more intuitive interactions with 3D objects. Five groups participated in our competition, submitting a total of 114 runs. While the results obtained in our competition are satisfactory, we note that the challenges presented by this task are far from being fully solved. As such, we provide insights into potential areas for future research and improvements. We believe that we can help push the boundaries of 3D object retrieval and facilitate more user-friendly interactions via vision-language technologies.Comment: arXiv admin note: text overlap with arXiv:2304.0573

Function of KAI2 signaling in plant drought adaptation

Drought causes substantial reductions in crop yields worldwide. Therefore, we set out to identify new chemical and genetic factors that regulate drought resistance in Arabidopsis thaliana. Karrikins (KARs) are a class of butenolide compounds found in smoke that promote seed germination, and have been reported to improve seedling vigor under stressful growth conditions. Here, we discovered that mutations in KARRIKIN INSENSITIVE2 (KAI2), encoding the proposed karrikin receptor, result in hypersensitivity to water deprivation. We performed transcriptomic, physiological and biochemical analyses of kai2 plants to understand the basis for KAI2-regulated drought resistance. We found that kai2 mutants have increased rates of water loss and drought-induced cell membrane damage, enlarged stomatal apertures, and higher cuticular permeability. In addition, kai2 plants have reduced anthocyanin biosynthesis during drought, and are hyposensitive to abscisic acid (ABA) in stomatal closure and cotyledon opening assays. We identified genes that are likely associated with the observed physiological and biochemical changes through a genome-wide transcriptome analysis of kai2 under both well-watered and dehydration conditions. These data provide evidence for crosstalk between ABA- and KAI2-dependent signaling pathways in regulating plant responses to drought. A comparison of the strigolactone receptor mutant d14 (DWARF14) to kai2 indicated that strigolactones also contributes to plant drought adaptation, although not by affecting cuticle development. Our findings suggest that chemical or genetic manipulation of KAI2 and D14 signaling may provide novel ways to improve drought resistance

Associations of Underlying Health Conditions With Anxiety and Depression Among Outpatients: Modification Effects of Suspected COVID-19 Symptoms, Health-Related and Preventive Behaviors

Objectives: We explored the association of underlying health conditions (UHC) with depression and anxiety, and examined the modification effects of suspected COVID-19 symptoms (S-COVID-19-S), health-related behaviors (HB), and preventive behaviors (PB).Methods: A cross-sectional study was conducted on 8,291 outpatients aged 18–85 years, in 18 hospitals and health centers across Vietnam from 14th February to May 31, 2020. We collected the data regarding participant's characteristics, UHC, HB, PB, depression, and anxiety.Results: People with UHC had higher odds of depression (OR = 2.11; p < 0.001) and anxiety (OR = 2.86; p < 0.001) than those without UHC. The odds of depression and anxiety were significantly higher for those with UHC and S-COVID-19-S (p < 0.001); and were significantly lower for those had UHC and interacted with “unchanged/more” physical activity (p < 0.001), or “unchanged/more” drinking (p < 0.001 for only anxiety), or “unchanged/healthier” eating (p < 0.001), and high PB score (p < 0.001), as compared to those without UHC and without S-COVID-19-S, “never/stopped/less” physical activity, drinking, “less healthy” eating, and low PB score, respectively.Conclusion: S-COVID-19-S worsen psychological health in patients with UHC. Physical activity, drinking, healthier eating, and high PB score were protective factors