Wind Turbine Fault-Tolerant Control via Incremental Model-Based Reinforcement Learning

A reinforcement learning (RL) based fault-tolerant control strategy is developed in this paper for wind turbine torque & pitch control under actuator & sensor faults subject to unknown system models. An incremental model-based heuristic dynamic programming (IHDP) approach, along with a critic-actor structure, is designed to enable fault-tolerance capability and achieve optimal control. Particularly, an incremental model is embedded in the critic-actor structure to quickly learn the potential system changes, such as faults, in real-time. Different from the current IHDP methods that need the intensive evaluation of the state and input matrices, only the input matrix of the incremental model is dynamically evaluated and updated by an online recursive least square estimation procedure in our proposed method. Such a design significantly enhances the online model evaluation efficiency and control performance, especially under faulty conditions. In addition, a value function and a target critic network are incorporated into the main critic-actor structure to improve our method’s learning effectiveness. Case studies for wind turbines under various working conditions are conducted based on the fatigue, aerodynamics, structures, and turbulence (FAST) simulator to demonstrate the proposed method’s solid fault-tolerance capability and adaptability. Note to Practitioners —This work achieves high-performance wind turbine control under unknown actuator & sensor faults. Such a task is still an open problem due to the complexity of turbine dynamics and potential uncertainties in practical situations. A novel data-driven and model-free control strategy based on reinforcement learning is proposed to handle these issues. The designed method can quickly capture the potential changes in the system and adjust its control policy in real-time, rendering strong adaptability and fault-tolerant abilities. It provides data-driven innovations for complex operational tasks of wind turbines and demonstrates the feasibility of applying reinforcement learning to handle fault-tolerant control problems. The proposed method has a generic structure and has the potential to be implemented in other renewable energy systems

Effect of Amorphization Methods on the Properties and Structures of Potato Starch-Monoglyceride Complex

Recently, starch-based fat replacers (FRs) have emerged as unique ingredients, possessing few calories and high vascular scavenger function without adverse organoleptic changes. Here, a two-step modification method for the development of a starch-based FRs is reported. First, native potato starch is amorphized by grinding, alkali and ethanol treatment. Then, the amorphized starch is complexed with monoglyceride. The results show that alkaline amorphous potato starch (AAPS) has the best emulsifying activity; ethanol amorphous potato starch complex (EAPSC) has the highest content of resistant starch (RS) (21.49%), while grinding amorphous potato starch (GAPS) retains the granular structure of the original starch best. The amorphization reduces the amylose content of starch, leading to reduced swelling power and increased digestibility. Complexation, on the other hand, is more like attaching a layer of the hydrophobic membrane. Combined with DSC and XRD, amorphization reduces the value of enthalpy and crystallinity, while the complexation process does the opposite. Overall, EAPSC is the best candidate for novel FRs, due to its greater emulsion stability and enzyme resistance. The experimental results provide a theoretical basis for the application of a novel potato starch-monoglyceride complex in foods such as cakes and snack fillings

Urbanization increased river nitrogen export to western Taiwan Strait despite increased retention by nitrification and denitrification

Abstract(#br)Urban development and increased human activities impose major environmental stress on the receiving bodies of water. Although urban rivers have been recognized as hotspots of regional nitrogen (N) pollution, detailed measurements of river nutrient species in response to urbanization are rarely reported, so the impacts of urban development on N cycling processes and transport to coast remains unclear. Here we investigated the changes in N species (concentration, composition and isotope) and N functional genes between upstream and downstream sections of several rivers affected by urban development in western Taiwan Strait under various flow conditions (low, medium and high flow). Our results suggest that urban sewage (high ammonium) is the predominant substrate that stimulated nitrification and subsequently denitrification and gaseous N removal (N 2 O, N 2 ). Nitrifying and denitrifying functional genes increased their abundance along the urban rivers. There were hydrological and meteorological controls on urban rivers regulating changes in nitrogen retention between seasons. Overall, the enhanced microbe-driven N retention could not balance the increase of urban N loading. Consequently, urbanization increased riverine N export and caused other changes in nutrient supply such as changing the nutrient ratio (N:P:Si ratio), increasing the potential for eutrophication both in the river and in receiving coastal ecosystems

Word Searching in Scene Image and Video Frame in Multi-Script Scenario using Dynamic Shape Coding

Retrieval of text information from natural scene images and video frames is a challenging task due to its inherent problems like complex character shapes, low resolution, background noise, etc. Available OCR systems often fail to retrieve such information in scene/video frames. Keyword spotting, an alternative way to retrieve information, performs efficient text searching in such scenarios. However, current word spotting techniques in scene/video images are script-specific and they are mainly developed for Latin script. This paper presents a novel word spotting framework using dynamic shape coding for text retrieval in natural scene image and video frames. The framework is designed to search query keyword from multiple scripts with the help of on-the-fly script-wise keyword generation for the corresponding script. We have used a two-stage word spotting approach using Hidden Markov Model (HMM) to detect the translated keyword in a given text line by identifying the script of the line. A novel unsupervised dynamic shape coding based scheme has been used to group similar shape characters to avoid confusion and to improve text alignment. Next, the hypotheses locations are verified to improve retrieval performance. To evaluate the proposed system for searching keyword from natural scene image and video frames, we have considered two popular Indic scripts such as Bangla (Bengali) and Devanagari along with English. Inspired by the zone-wise recognition approach in Indic scripts[1], zone-wise text information has been used to improve the traditional word spotting performance in Indic scripts. For our experiment, a dataset consisting of images of different scenes and video frames of English, Bangla and Devanagari scripts were considered. The results obtained showed the effectiveness of our proposed word spotting approach.Comment: Multimedia Tools and Applications, Springe

Efficacy and safety of a combination of miglitol, metformin and insulin aspart in the treatment of type 2 diabetes

Purpose: To study the clinical effect of combining insulin aspart with different drugs in the treatment oftype 2 diabetes mellitus (T2DM).Methods: Two hundred and thirty-seven T2DM patients admitted to the Endocrinology Department of the Second Affiliated Hospital of Kunming Medical University from March to September 2018 were selected as subjects in this study. Miglitol and metformin were used in combination with insulin aspart in the treatment of T2DM. In addition, data on the effectiveness and safety of different treatment options,such as patient’s weight, waist circumference, blood glucose indicators, indices of heart, liver and kidney functions, and incidence of complications were recorded and compared between the two groups.Results: The use of a combination of miglitol and insulin aspart produced an excellent hypoglycaemic effect, and it significantly reduced the incidence of sensory neuropathy in the eyes and distal limbs (p < 0.05). The use of combination of metformin and insulin aspart effectively protected the heart and kidney, and prevented hypoglycaemia (p < 0.05).Conclusion: These results suggest that treatment with a combination of miglitol and insulin aspart is suitable for patients with T2DM whose blood sugar levels are out of control, while combined treatment with metformin and insulin aspart is more suited for patients who desire to reduce blood sugar and blood lipids through weight loss, and patients with cardiac and renal insufficiency

Add-On Effect of Chinese Herbal Medicine Bath to Phototherapy for Psoriasis Vulgaris: A Systematic Review

Psoriasis vulgaris is the most common form of psoriasis. Phototherapy has been proven effective for psoriasis, but side effects have become a concern. Chinese herbal medicine (CHM) bath combined with phototherapy has been used in clinical settings, but the additional benefit requires evaluation. This review aims to evaluate the additional benefit and safety of adding CHM bath to phototherapy for psoriasis vulgaris. Cochrane library, PubMed, Embase, CNKI, and CQVIP were searched from their inceptions to 6 August 2012. Randomized controlled trials (RCTs) comparing CHM bath plus phototherapy to phototherapy alone for psoriasis vulgaris were included. Data was analyzed using Review Manager 5.1.0. Thirteen RCTs were included in the review, and eight were included in the meta-analysis. Meta-analysis showed higher efficacy of CHM bath plus phototherapy when compared with phototherapy alone in terms of PASI 60 (RR 1.25; 95% CI: 1.18–1.32). Mild adverse events were reported in ten studies, but these could be alleviated by reducing UV dosage or applying emollient. In conclusion, CHM bath appears to be a beneficial and safe adjunctive therapy to phototherapy for psoriasis vulgaris. However, these results should be interpreted with caution due to the low methodological quality of the included studies

Benefits and Models of Sexual Health Services Provided by General Practitioners

Sexual health is an important component of human health. Ignoring, misunderstanding and having misconceptions of sexual health will greatly impair people's quality of life. Owing to the concept of holistic health in general medicine, influence of biopsychosocial model of health, and family as a vital unit of care, and adherence to protecting patient privacy as a professional responsibility, general practitioners (GPs) have obvious advantages in offering sexual health services. However, more efforts are needed to strengthen the promotion of sexual healthcare knowledge popularization, sexual health screening, and sexual problem diagnosis and treatment in primary care of China. To provide support for Chinese GPs to deliver sexual health services, Department of General Medicine, the University of Hong Kong-Shenzhen Hospital, has pioneered in providing sexual health services and exploring new service delivery models using actions such as constructing a sexual health service team and a genital examination skills workshop, carrying out the consultation about sexual history, and developing a standard diagnostic and therapeutic procedure for sexualproblems

Decoding the dopamine transporter imaging for the differential diagnosis of parkinsonism using deep learning.

PURPOSE This work attempts to decode the discriminative information in dopamine transporter (DAT) imaging using deep learning for the differential diagnosis of parkinsonism. METHODS This study involved 1017 subjects who underwent DAT PET imaging ([11C]CFT) including 43 healthy subjects and 974 parkinsonian patients with idiopathic Parkinson's disease (IPD), multiple system atrophy (MSA) or progressive supranuclear palsy (PSP). We developed a 3D deep convolutional neural network to learn distinguishable DAT features for the differential diagnosis of parkinsonism. A full-gradient saliency map approach was employed to investigate the functional basis related to the decision mechanism of the network. Furthermore, deep-learning-guided radiomics features and quantitative analysis were compared with their conventional counterparts to further interpret the performance of deep learning. RESULTS The proposed network achieved area under the curve of 0.953 (sensitivity 87.7%, specificity 93.2%), 0.948 (sensitivity 93.7%, specificity 97.5%), and 0.900 (sensitivity 81.5%, specificity 93.7%) in the cross-validation, together with sensitivity of 90.7%, 84.1%, 78.6% and specificity of 88.4%, 97.5% 93.3% in the blind test for the differential diagnosis of IPD, MSA and PSP, respectively. The saliency map demonstrated the most contributed areas determining the diagnosis located at parkinsonism-related regions, e.g., putamen, caudate and midbrain. The deep-learning-guided binding ratios showed significant differences among IPD, MSA and PSP groups (P < 0.001), while the conventional putamen and caudate binding ratios had no significant difference between IPD and MSA (P = 0.24 and P = 0.30). Furthermore, compared to conventional radiomics features, there existed average above 78.1% more deep-learning-guided radiomics features that had significant differences among IPD, MSA and PSP. CONCLUSION This study suggested the developed deep neural network can decode in-depth information from DAT and showed potential to assist the differential diagnosis of parkinsonism. The functional regions supporting the diagnosis decision were generally consistent with known parkinsonian pathology but provided more specific guidance for feature selection and quantitative analysis

NAT10 Maintains OGA mRNA Stability Through ac4C Modification in Regulating Oocyte Maturation

In vitro maturation (IVM) refers to the process of developing immature oocytes into the mature in vitro under the microenvironment analogous to follicle fluid. It is an important technique for patients with polycystic ovary syndrome and, especially, those young patients with the need of fertility preservation. However, as the mechanisms of oocyte maturation have not been fully understood yet, the cultivation efficiency of IVM is not satisfactory. It was confirmed in our previous study that oocyte maturation was impaired after N-acetyltransferase 10 (NAT10) knockdown (KD). In the present study, we further explored the transcriptome alteration of NAT10-depleted oocytes and found that O-GlcNAcase(OGA) was an important target gene for NAT10-mediated ac4C modification in oocyte maturation. NAT10 might regulate OGA stability and expression by suppressing its degradation. To find out whether the influence of NAT10-mediated ac4C on oocyte maturation was mediated by OGA, we further explored the role of OGA in IVM. After knocking down OGA of oocytes, oocyte maturation was inhibited. In addition, as oocytes matured, OGA expression increased and, conversely, O-linked N-acetylglucosamine (O-GlcNAc) level decreased. On the basis of NAT10 KD transcriptome and OGA KD transcriptome data, NAT10-mediated ac4C modification of OGA might play a role through G protein–coupled receptors, molecular transduction, nucleosome DNA binding, and other mechanisms in oocyte maturation. Rsph6a, Gm7788, Gm41780, Trpc7, Gm29036, and Gm47144 were potential downstream genes. In conclusion, NAT10 maintained the stability of OGA transcript by ac4C modification on it, thus positively regulating IVM. Moreover, our study revealed the regulation mechanisms of oocytes maturation and provided reference for improving IVM outcomes. At the same time, the interaction between mRNA ac4C modification and protein O-GlcNAc modification was found for the first time, which enriched the regulation network of oocyte maturation