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A gallium nitride (GaN) boundary conduction mode (BCM) dual-boost ac–dc converter for low-voltage electromagnetic energy harvesting (EH) is presented in this article. The μ W-to-mW EH system is very susceptible to any tiny losses from power converters, interconnections, and system parasitic. To have better utilizations of harvested energy, an output power enhanced power conversion design is proposed. First, impedance matching is satisfied between electromagnetic generator and ac–dc converter to achieve maximum delivered power. The ac–dc converter is designed under BCM for constant input impedance. EH's winding inductance is employed as the boost inductor in the ac–dc converter. A codesign principle for converter on -time with electromagnetic generator's winding characteristics is revealed. Second, power transistors in EH low-voltage conversion are optimized to realize high efficiency. Power transistors’ low-voltage switching characteristics are significantly different from high-voltage situation with no or little miller plateau region. Low-voltage power transistors are compared from both device characteristics and calculated power loss to provide device selection guidance. A GaN-based dual-boost ac–dc converter under BCM operation with constant on -time controller is designed in this article to provide 3.3 V output for a 500-Ω load resistor. It achieves peak efficiency of 82.4% for open-loop operation at 0.6 V/100 Hz input and peak efficiency of 72.3% for close-loop operation at 0.75 V/100 Hz.

Background: Long-term morphine use is associated with serious side effects, such as morphine-induced hyperalgesia and analgesic tolerance. Previous investigations have documented the association between dopamine (DA) neurons in the ventral tegmental area (VTA) and pain. However, whether VTA DA neurons are implicated in morphine-induced hyperalgesia and analgesic tolerance remains elusive. Methods: Initially, we observed behavioural effects of lidocaine administration into VTA or ablation of VTA DA neurons on morphine-induced hyperalgesia and anti-nociceptive tolerance. Subsequently, c-Fos expression in nucleus accumbens (NAc) shell-projecting and medial prefrontal cortex (mPFC)-projecting VTA DA neurons after chronic morphine treatment was respectively investigated. Afterwards, the effects of chemogenetic manipulation of NAc shell-projecting or mPFC-projecting DA neurons on morphine-induced hyperalgesia and anti-nociceptive tolerance were observed. Additionally, effects of chemogenetic manipulation of VTA GABA neurons on c-Fos expression in VTA DA neurons were investigated. Results: Lidocaine injection into VTA relieved established hyperalgesia and anti-nociceptive tolerance whereas ablation of VTA DA neurons prevented the development of morphine-induced hyperalgesia and anti-nociceptive tolerance. Chronic morphine treatment increased c-Fos expression in NAc shell-projecting DA neurons, rather than in mPFC-projecting DA neurons. Chemogenetic manipulation of NAc shell-projecting DA neurons had influence on morphine-induced hyperalgesia and tolerance. However, chemogenetic manipulation of mPFC-projecting DA neurons had no significant effects on morphine-induced hyperalgesia and anti-nociceptive tolerance. Chemogenetic manipulation of VTA GABA neurons affected the c-Fos expression in VTA DA neurons. Conclusions: These findings revealed the involvement of NAc shell-projecting VTA DA neurons in morphine-induced hyperalgesia and anti-nociceptive tolerance, and may shed new light on the clinical management of morphine-induced hyperalgesia and analgesic tolerance. Perspective: This study demonstrated that NAc shell-projecting DA neurons rather than mPFC-projecting DA neurons in the VTA were implicated in morphine-induced hyperalgesia and anti-nociceptive tolerance. Our findings may pave the way for the discovery of novel therapies for morphine-induced hyperalgesia and analgesic tolerance.

Recent approaches for predicting layouts from 360 $$^{\circ }$$ panoramas produce excellent results. These approaches build on a common framework consisting of three steps: a pre-processing step based on edge-based alignment, prediction of layout elements, and a post-processing step by fitting a 3D layout to the layout elements. Until now, it has been difficult to compare the methods due to multiple different design decisions, such as the encoding network (e.g., SegNet or ResNet), type of elements predicted (e.g., corners, wall/floor boundaries, or semantic segmentation), or method of fitting the 3D layout. To address this challenge, we summarize and describe the common framework, the variants, and the impact of the design decisions. For a complete evaluation, we also propose extended annotations for the Matterport3D dataset (Chang et al.: Matterport3d: learning from rgb-d data in indoor environments. arXiv:1709.06158 , 2017), and introduce two depth-based evaluation metrics.

Ganoderma is one of the common medicinal mushrooms in traditional Chinese medicine. Previous researches have unveiled the multifaceted biological activity of Ganoderma extract. Ganoderma tsugae has been investigated the potential on curing prostate, colon, lung, epidermoid, breast and ovarian cancers, but not including endometrial cancer. Endometrial cancer is a gynecological malignant tumor with serious drug resistance problem in clinical cancer treatment. This study aimed to demonstrate the first study of Ganoderma on treating endometrial cancer. The Ganoderma tsugae ethanol extract (GTEE) could suppress the proliferation of endometrial cancer cells HEC-1-A, KLE, and AN3 CA. GTEE also induced G1/S phase arrest and mitochondria-mediated apoptosis in endometrial cancer cells. Furthermore, the Akt signaling pathway could be suppressed by GTEE. Therefore, our results suggest for the first time that GTEE has the potential to be an adjuvant therapeutic agent in the treatment of endometrial cancer.

Clustering ensemble technique has been shown to be effective in improving the accuracy and stability of single clustering algorithms. With the development of information technology, the amount of data, such as image, text and video, has increased rapidly. Efficiently clustering these large-scale datasets is a challenge. Clustering ensembles usually transform clustering results to a co-association matrix, and then to a graph-partition problem. These methods may suffer from information loss when computing the similarity among samples or base clusterings. Rich information between samples and base clusterings is ignored. Moreover, the results are not discrete. They need post-processing steps to obtain the final clustering result, which will deviate greatly from the real clustering result. To address this problem, we propose a co-clustering ensemble based on bilateral k-means (CEBKM) algorithm. Our algorithm can simultaneously cluster samples and base clusterings of a dataset, to fully exploit the potential information between the samples and the base clusterings. In addition, it can directly obtain the final clustering results without using other clustering algorithms. The proposed method, outperformed several state-of-the-art clustering ensemble methods in experiments conducted on real-world and toy datasets.

Recently, physically unclonable functions (PUFs) have received considerable attention from the research community due to their potential use in security mechanisms for applications such as the Internet of things (IoT). The concept generally employs the fabrication variability and naturally embedded randomness of device characteristics for secure identification. This approach complements and improves upon the conventional cryptographic security algorithms by covering their vulnerability against counterfeiting, cloning attacks, and physical hijacking. In this work, we propose a new identification/authentication mechanism based on a specific implementation of optical PUFs based on electrochemically formed dendritic patterns . Dendritic tags are built by growing unique, complex, and unclonable nano-scaled metallic patterns on highly nonreactive substrates using electrolyte solutions. Dendritic patterns with 3D surfaces are technically impossible to reproduce, hence they can be used as the fingerprints of objects. Current optical PUF-based identification mechanisms rely on image processing methods that require high-complexity computations and massive storage and communication capacity to store and exchange high-resolution image databases in large-scale networks. To address these issues, we propose a light-weight identification algorithm that converts the images of dendritic patterns into representative graphs and uses a graph-matching approach for device identification. More specifically, we develop a probabilistic graph matching algorithm that makes linkages between the similar feature points in the test and reference graphs while considering the consistency of their local subgraphs. The proposed method demonstrates a high level of accuracy in the presence of imaging artifacts, noise, and skew compared to existing image-based algorithms. The computational complexity of the algorithm grows linearly with the number of extracted feature points and is therefore suitable for large-scale networks.

Contains fulltext : 251344.pdf (Publisher’s version ) (Open Access) The discrepancy between chronological age and the apparent age of the brain based on neuroimaging data - the brain age delta - has emerged as a reliable marker of brain health. With an increasing wealth of data, approaches to tackle heterogeneity in data acquisition are vital. To this end, we compiled raw structural magnetic resonance images into one of the largest and most diverse datasets assembled (n=53542), and trained convolutional neural networks (CNNs) to predict age. We achieved state-of-the-art performance on unseen data from unknown scanners (n=2553), and showed that higher brain age delta is associated with diabetes, alcohol intake and smoking. Using transfer learning, the intermediate representations learned by our model complemented and partly outperformed brain age delta in predicting common brain disorders. Our work shows we can achieve generalizable and biologically plausible brain age predictions using CNNs trained on heterogeneous datasets, and transfer them to clinical use cases.

Maximum Power Point Tracking (MPPT) approaches have been widely applied in energy harvesting systems. However, such control algorithms such as Perturb-and Observe (P&O) method usually require DSP or customized control ICs. This leads to high power consumption and high cost. This paper proposes a novel strategy to realize max. power delivery through coil connection switch approach where the input impedances and voltage/current levels are adjusted according to different output voltages. A single stage AC-DC dual boost converter is employed with fixed duty cycle to charge a super-capacitor load to verify the concept. Three sets of harvester coils are used and are connected in either parallel or series. The switch of coil connections is realized through isolated analog switches. It is demonstrated that the harvester with dual boost converter under proposed strategy achieves an maximum output power of 3.628 mW in 0.2 g acceleration, which is 41.7% higher than same converter without coil connection switching. With proposed method, the output power reaches to 98.7% of the output power with traditional P&O MPPT strategy. It also achieves higher efficiency and more compact system size than traditional P&O MPPT.

A start-up system for AC-DC converter in low voltage electromagnetic energy harvesting (EMEH) is presented in this paper. Power conversion circuit is required in EMEH to regulator the low voltage AC to a stable DC output. Switchable AC-DC converter is efficient and well controllable, making it an optimal choice. However, the gate driver and control circuits in AC-DC converter needs to start up prior to main power stage. The output amplitude of EMEH is usually quite low to power these circuits directly through passive rectifier. Hence, a self-start-up circuit will be an optimal choice. Furthermore, in such a low power system, the power consumptions of low power control and logic circuits are comparable to actual output power. To have better utilizations of the harvested power, the power distributions of the whole power conversion is worth investigating. In this paper, an output regulated voltage multiplier based start-up circuit (SUC) is employed with comprehensive design considerations from output gain, charging time and efficiency. The AC-DC converter is firstly started through SUC. Once stable output is established, the output of AC-DC converter is employed to provide power to control circuits and the start-up circuit is cut off to reduce unnecessary energy consumption.

In this paper, a single stage hybrid dual-mode AC-DC circuit for vibration energy harvesting (EH) is presented. The circuit combines a traditional voltage multiplying (VM) circuit and boost regulator, utilizing the winding inductance from the electromagnetic energy harvester. The proposed circuit converts the AC voltage generated from VM to power the load and stores energy in the super-capacitor when external vibration exists. When external vibration disappears, it will continue powering the load using the energy stored in super-capacitor through boost regulator. Traditional two-stage power regulation of energy harvesting based power supply is reduced to one-stage for smaller system size. Furthermore, the start-up transient is expedited through cooperation of VM and boost regulator. A GaN HEMT and Si schottky diodes based prototype is built to demonstrate the performances. Different operation modes are fully verified. The proposed circuit achieves 3.3V/1.089mW output with designed electromagnetic energy harvester under vibration frequency of 85Hz and acceleration of 0.7g. It can maintain stable output for 30s during the disappearance of vibration. The peak output efficiency of the converter reaches to 85.9%.

Probiotics are expected to be an ideal alternative for antibiotics in the poultry industry. This study aimed to investigate the effect of Lactobacillus plantarum on growth traits, slaughter performance, serum markers and intestinal bacterial community of Daheng broilers. A total of 2400 healthy one-day-old Daheng broilers were randomly divided into 5 groups with 6 replicates per group and 40 individuals per replicate. Birds in control group were fed a basal diet, and others were fed basal diets supplemented with 105 , 106 , 107 and 108 CFU/kg Lactobacillus plantarum, respectively. It turned out that adding Lactobacillus plantarum to diet could significantly improve the serum immune performance of broilers (p 0.05), but had no significant effect on growth traits and slaughter performance. Moreover, Lactobacillus plantarum could improve the diversity of intestinal bacterial community, but with the increase of addition concentration, the diversity would gradually decrease. In conclusion, Lactobacillus plantarum can be used as feed additive in broiler production, but whether it is more effective than antibiotics needs further investigation.

Background: Studies exploring on the relationship between blood pressure fluctuations and outcome in acute ischemic stroke (AIS) patients treated with intravenous thrombolysis (IVT) are limited. We aimed to investigate the influence of blood pressure variability (BPV) during the first 24 hours after IVT on neurological deterioration (END) and 3-month outcome after IVT in patients with symptomatic intracranial arterial stenosis or occlusion (SIASO).Methods: Clinical data from consecutive AIS patients with SIASO who received IVT were retrospectively analyzed. The hourly systolic BP of all patients were recorded during the first 24 hours following IVT. We calculated three syslolic BPV parameters including coefficient of variability (CV), standard deviation of mean BP (SD) and successive variation (SV). The SV was categorized into four grades based on quartiles. The END was defined as neurological deterioration with an increase in the National Institutes of Health Stroke Scale (NIHSS) score ≥ 4 points within the first 72 hours after admission. Follow-ups was performed at 90 days after onset were performed, and favorable and poor outcome were defined as a modified Rankin Scale scores of ≤1 or ≥2, respectively.Results: A total of 110 patients were included, with a mean age of 62.0 ± 12.5 years. 86 patients (78.2%) were male. Twenty patients (18.2%) experienced END, and 37 patients (33.6%) had a favorable outcome. Compared with patients with in the poor outcome group, age ([64.8 ± 10.9] vs [56.7 ± 13.8]), NIHSS on admission (11.0 [7.0 -16.0] vs 6.0 [3.5 - 9.0]), SV ([14.5 ± 4.3] vs [11.8 ± 3.2]) and SD ([12.7 ± 3.8] vs [10.9 ± 3.3]) were lower in the favorable outcome group (all p < 0.05). No BPV parameters were associated with END. In the multivariable logistic regression analysis, compared with the lowest SV (SV50%-75% (odds rato [OR] = 4.449, 95% confidence interval [CI] = 1.231-16.075, p = 0.023) and SV>75% (OR = 8.676, 95% CI = 1.892-39.775, p = 0.005) were significantly associated with poor outcome at 3 months. Conclusions: SV had a negative relationship with the 3-month outcome in AIS patients with SIASO treated with IVT, indicating that BPV may affect the outcome of AIS.

In the carbon capture and storage (CCS) infrastructure, the risk of a high-pressure buried pipeline rupture possibly leads to catastrophic accidents due to the release of tremendous amounts of carbon dioxide (CO2). Therefore, a comprehensive understanding of the effects of CO2 dispersion pattern after release from CCS facilities is essential to allow the appropriate safety precautions to be taken. Due to variations in topography above the pipeline, the pattern of CO2 dispersion tends to be affected by the real terrain features, such as trees and hills. However, in most previous studies, the dynamic impact of trees on the wind field was often approximated to linear treatment or even ignored. In this article, a computational fluid dynamics (CFD) model was proposed to predict CO2 dispersion over shrubbery areas. The shrubs were regarded as a kind of porous media, and the model was validated against the results from experiment. It was found that shrubbery affected the flow field near the ground, enhancing the lateral dispersion of CO2. Compared with that of the shrub-free terrain, the coverage area of the three shrub terrains at 60 s increased by 8.1 times, 6.7 times, and 9.1 times, respectively. The influence of shrub height and porosity on CO2 dispersion is nonlinear. This research provides reliable data for the risk assessment of CCS.

Brain age prediction from brain MRI scans not only helps improve brain ageing modelling generally, but also provides benchmarks for predictive analysis methods. Brain-age delta, which is the difference between a subject's predicted age and true age, has become a meaningful biomarker for the health of the brain. Here, we report the details of our brain age prediction models and results in the Predictive Analysis Challenge 2019. The aim of the challenge was to use T1-weighted brain MRIs to predict a subject's age in multicentre datasets. We apply a lightweight deep convolutional neural network architecture, Simple Fully Convolutional Neural Network (SFCN), and combined several techniques including data augmentation, transfer learning, model ensemble, and bias correction for brain age prediction. The model achieved first place in both of the two objectives in the PAC 2019 brain age prediction challenge: Mean absolute error (MAE) = 2.90 years without bias removal (Second Place = 3.09 yrs; Third Place = 3.33 yrs), and MAE = 2.95 years with bias removal, leading by a large margin (Second Place = 3.80 yrs; Third Place = 3.92 yrs).

Spinal cord injury (SCI) routinely causes the immediate loss and disruption of neurons followed by complicated secondary injuries, including inflammation, oxidative stress, and dense glial scar formation. Inhibitory factors in the lesion scar and poor intrinsic neural regeneration capacity restrict functional recovery after injury. Minocycline, which has neuroprotective activity, can alleviate secondary injury, but the long-term administration of this drug may cause toxicity. Polysialic acid (PSA) is a large cell-surface carbohydrate that is critical for central nervous system development and is capable of promoting precursor cell migration, axon path finding, and synaptic remodeling; thus, PSA plays a vital role in tissue repair and regeneration. Here, we developed a PSA-based minocycline-loaded nanodrug delivery system (PSM) for the synergistic therapy of spinal cord injury. The prepared PSM exerted marked anti-inflammatory and neuroprotective activities both in vitro and in vivo. The administration of PSM could significantly protect neurons and myelin sheaths from damage, reduce the formation of glial scar, recruit endogenous neural stem cells to the lesion site, and promote the regeneration of neurons and the extension of long axons throughout the glial scar, thereby largely improving the locomotor function of SCI rats and exerting a superior therapeutic effect. The findings might provide a novel strategy for SCI synergistic therapy and the utilization of PSA in other central nervous system diseases.

Avionics Application Standard Software Interface (ARINC 653) is a software specification for space and time partitioning in safety-critical avionics real-time operating systems. Correctly designed task schedulers are crucial for ARINC 653 running systems. This paper proposes a model-checking-based method for analyzing and verifying ARINC 653 scheduling model. Based on priced timed automata theory, an ARINC 653 scheduling system was modeled as a priced timed automata network. The schedulability of the system was described as a set of temporal logic expressions, and was analyzed and verified by a model checker. Our research shows that it is feasible to use model checking to analyze task schedulability in an ARINC 653 hierarchical scheduling system. The method discussed modeled preemptive scheduling by using the stop/watch features of priced timed automata. Unlike traditional scheduling analysis techniques, the proposed approach uses an exhaustive method to automate analysis of the schedulability of a system, resulting in a more precise analysis

Supplemental Digital Content is available in the text., Background and Purpose— The aim of the study was to assess the effect of lesion severity in cortical cholinergic pathways in acute ischemic stroke patients on functional outcomes. Methods— The study sample consisted of 214 men (70.9%) and 88 women (29.1%) with acute ischemic stroke. We used the Cholinergic Pathways Hyperintensities Scale (CHIPS) to assess the severity of lesions in cortical cholinergic pathways using brain magnetic resonance imaging. The other magnetic resonance imaging parameters included infarction, white matter lesions, and medial temporal lobe atrophy. Functional outcome was assessed using the Lawton activities of daily living (ADL) scale at 3 and 6 months after the index stroke. We also assessed disability status using the modified Rankin Scale. Results— Univariate analysis showed that patients with poor functional outcomes were older, more likely to be men, had a higher National Institutes of Health Stroke Scale (NIHSS) score on admission, and had more frequent histories of previous stroke and infection complications. They also had significantly more frequent cortical infarcts, left subcortical infarcts, a larger infarct volume, more severe medial temporal lobe atrophy, and periventricular hyperintensities, and higher CHIPS scores. In the multiple regression analysis, model 1 showed that age and NIHSS score on admission were significant predictors of poor ADL at 3 months, with an R2 of 45.4% fitting the model. Age, NIHSS score on admission and stroke subtype were also significant predictors of poor ADL at 6 months, with an R2 of 37.9% fitting the model. In model 2, sex, previous stroke, NIHSS score on admission, right cortical infarcts, left subcortical infarcts and CHIPS score were significant predictors for poor ADL at 3 months, with an R2 of 53.5%. NIHSS score on admission, stroke subtype, and CHIPS score were significant predictors for poor ADL at 6 months, with an R2 of 40.2%. After adjustment for confounders, CHIPS score was also a significant predictor for poor modified Rankin Scale, both at 3 and 6 months. Even after removing patients with moderate-to-severe white matter lesions, higher CHIPS scores still correlated with poorer ADL and modified Rankin Scale both at both 3 and 6 months. Conclusions— In patients with acute ischemic stroke, cortical cholinergic pathways impairment is common, and the severity of lesions in the cortical cholinergic pathways may significantly predict a poorer functional outcome. Clinical Trial Registration— URL: http://www.chictr.org.cn/index.aspx. Unique identifier: ChiCTR1800014982.

A compact self-power module is proposed in this paper with the tubular integration of electromagnetic vibration energy harvester and voltage multiplier. The electromagnetic energy harvester is constructed with dual planar springs and cylindrical magnets. The optimal location and size of the coils are investigated. A single-stage voltage multiplier is used to rectifier and boost the harvested AC voltage, which is also followed by a LDO stage to further stabilize the output. The volume of the electromagnetic vibration energy harvester is 8 cm3. The maximum output power is 19.1mW when the acceleration is 0.7 g and the resonance frequency is 116 Hz. The designed self-power module is able to provide stable voltage and sufficient power for the wireless temperature and humidity sensor.

Background Transarterial chemoembolization (TACE) is an effective locoregional therapy in hepatocellular carcinoma (HCC). However, it is difficult to predict the tumour response (TR) of TACE intraprocedurally. The aim of this study was to predict the TR after TACE (1–3 months) in HCC patients using intraprocedural intraarterial contrast enhanced ultrasound (IA-CEUS). Methods In this case-control study, consecutive patients who received TACE in our hospital from September 2018 to May 2019 were enrolled. IA-CEUS was performed before and after TACE. Postoperative contrast-enhanced liver MRI was performed 1–3 months after TACE as the gold standard. According to the modified Response Evaluation Criteria in Solid Tumours (mRECIST), ultrasonic manifestations were compared between the complete remission (CR) group and non-CR group by univariate and multivariate analyses. A logistic predictive model was established and validated, and its diagnostic efficiency was evaluated. Results Forty-four patients with sixty-one lesions were enrolled in the study. Multivariate analysis identified, the risk factors as a large lesion diameter (OR: 1.84; 95% confidence interval [CI]: 1.009, 3.080; P = 0.020), a larger dimension of non-enhancing area in superior mesenteric artery (SMA)-CEUS than the size in B-mode ultrasound preoperatively (OR: 3.379; 95% CI: 1.346,8.484; P = 0.010), presence of corona enhancement in hepatic artery (HA)-CEUS postoperatively (OR: 6.642; 95% CI: 1.214, 36.331; P = 0.029), and decreased corona enhancement thickness (per centimetre) postoperatively (OR: 0.025; 95% CI: 0.006,0.718; P = 0.025). The area under the receiver operating characteristic curve (AUROC) of the predictive model was 0.904 (95% CI: 0.804, 0.966; P Conclusions Intraprocedural IA-CEUS can be used to predict the TR in HCC patients after TACE.

In the middle or late stage of oilfield exploitation in China, the storage speed of oil well does not match pumping speed, resulting in pumping unit in the state of “non-full pumping” or “empty pumping”, which wastes lots of electricity. This paper used overdetermined equation and neural networks to predict liquid production after eliminating dimensional influence among oil well feature data with normalization method. Comparing the results with the regression equation, the effect of neural network is better than the other two methods in the case of large amounts of data. Even under the same training set, the results of the two neural networks are quite different. According to the prediction results of regular data, the effect of neural networks are significantly affected by the characteristics and quantity of the sample data. Therefore, appropriate prediction method in the prediction of liquid production can provide reference for oilfield management.

Poria cocos, called fuling, is a famous tonic in traditional Chinese medicine that reportedly possesses various pharmacological properties, including anti-inflammation and immunomodulation. However, few studies have investigated the effects of P. cocos on allergic diseases, such as allergic asthma. Allergic asthma is caused primarily by Th2 immune response and characterized by airway inflammation. This study first demonstrated the anti-allergic and anti-asthmatic effects of P. cocos extract (Lipucan®). P. cocos extract distinctly exhibited reduced inflammatory cell infiltration in the peribronchial and peribronchiolar regions compared to the asthma group in the histological analysis of pulmonary tissue sections. Prolonged P. cocos extract administration significantly reduced eosinophil infiltration, PGE2 levels, total IgE, and OVA-specific IgE. Moreover, P. cocos extract markedly suppressed Th2 cytokines, IL-4, IL-5, and IL-10. On the other hand, P. cocos extract significantly elevated IL-2 secretion by Th1 immune response. In addition, P. cocos extract elevated the IFN-γ level at a lower dose. We also observed that P. cocos extract increased the activity of NK cells. Our results suggest that P. cocos extract remodels the intrinsic Th1/Th2 response to prevent or alleviate allergy-induced asthma or symptoms.

Cone-rod dystrophy (CORD) is one of the inherited retinal diseases that result in central visual field deterioration and decreased visual acuity (VA). In CORD patients, impaired photoreceptor cells are observed as the disruption of ellipsoid zone (EZ) on optical coherence tomography (OCT) images. In the present study, we calculated the index of residual EZ (rEZ) to quantify the function of photoreceptor cells and investigated the correlation between rEZ index and visual functions. Twenty-six eyes of 13 patients with clinical suspicion of CORD were examined. Visual field was tested with the Humphrey Visual Field Analyzer (HFA 10-2 program). We simultaneously obtained OCT images and calculated the area of decreased EZ intensity (EZa). Using the binarized OCT images, the percentage of the rEZ in a 3 × 3 mm area surrounding the macula was analyzed. To clarify interrator reproducibility, intraclass correlation coefficient (ICC) was calculated. Moreover, we investigated the association between OCT parameters and VA as well as the mean deviation (MD) value measured with HFA. The mean age of the patients was 48.5 ± 16.9 years. The mean central retinal thickness was 122.7 ± 73.2 μm. The mean EZa and rEZ were 22.2 ± 23.6 μm2 and 0.35 ± 0.31, respectively. The ICC of each rEZ index was 0.91 (95% CI: 0.89

Integrated electronic design project which allows students to carry out engineering design based on theoretical knowledge is one of the most important basic courses in electronic and information engineering majors in universities. Based on the analysis of existing issues, this article explores some reforms of the course in combination with the demands of talents in the electronic information industry. Explorations and reforms of integrated electronic design project are mainly focus on reforming the teaching content, reforming teaching method, strengthening the cultivation of students' comprehensive ability, reforming assessment method of student, and strengthening the construction of teacher team.

Deep learning has huge potential for accurate disease prediction with neuroimaging data, but the prediction performance is often limited by training-dataset size and computing memory requirements. To address this, we propose a deep convolutional neural network model, Simple Fully Convolutional Network (SFCN), for accurate prediction of brain age using T1-weighted structural MRI data. Compared with other popular deep network architectures, SFCN has fewer parameters, so is more compatible with small dataset size and 3D volume data. The network architecture was combined with several techniques for boosting performance, including data augmentation, pre-training, model regularization, model ensemble and prediction bias correction. We compared our overall SFCN approach with several widely-used machine learning models. It achieved state-of-the-art performance in UK Biobank data (N = 14,503), with mean absolute error (MAE) = 2.14y in brain age prediction and 99.5% in sex classification. SFCN also won (both parts of) the 2019 Predictive Analysis Challenge for brain age prediction, involving 79 competing teams (N = 2,638, MAE = 2.90y). We describe here the details of our approach, and its optimisation and validation. Our approach can easily be generalised to other tasks using different image modalities, and is released on GitHub.HighlightsA lightweight deep learning model, Simple Fully Convolutional Network (SFCN), is presented, achieving state-of-the-art brain age prediction and sex classification performance in UK Biobank MRI brain imaging data.Even with limited number of training subjects (e.g., 50), SFCN performs better than widely-used regression models.A semi-multimodal ensemble strategy is proposed and achieved first place in the PAC 2019 brain age prediction challenge.Linear regression can remove brain age prediction bias (even on unlabelled data) while maintaining state-of-the-art performance.

To study the effects of deep-ocean water concentrate (DOWC) on sake quality, Taichung No. 10 indica rice (Oryza sativa subsp. indica) and Tainan No. 11 japonica rice (O. sativa subsp. japonica) were used as raw materials, and basic physicochemical property parameters in shochu were analyzed differentially. Sake fermentation mash analysis results revealed that DOWC addition did not significantly affect the basic physicochemical properties during sake brewing, but it significantly reduced citric acid and malic acid contents in Taichung No. 10 indica rice sake sample by 52&ndash, 66% and 73&ndash, 93%, respectively. DOWC addition significantly increased citric acid content in Tainan No. 11 japonica rice sake sample by 32&ndash, 202%. Rice shochu analysis results revealed that DOWC addition significantly increased isoamyl acetate, ethyl hexanoate, and ethyl octanoate contents in shochu made from japonica rice and indica rice, respectively. The results indicate that rice variety directly affects the types of volatile compounds in rice shochu. Principal component analysis and sensory evaluation results revealed that DOWC addition affected the composition of volatile compounds in the two types of rice shochu and resulted in differences in flavor evaluation. DOWC addition affects yeast metabolites and directly changes the volatile compound composition and flavor of rice shochu.

Introduction Very few studies have investigated the specific relationship between neutrophil‐to‐lymphocyte ratio (NLR) and the short‐term outcomes of patients suffering from mild acute ischemic stroke (AIS) and receiving intravenous thrombolysis (IVT). This study aimed to investigate whether a high NLR is associated with a poor short‐term outcome in patients with mild AIS after IVT. Methods We retrospectively analyzed data that were prospectively acquired from patients with AIS treated with IVT. Mild AIS was defined as a National Institutes of Health Stroke Scale (NIHSS) score ≤ 7 on admission. The NLR was based on a blood test performed prior to IVT and was classified as ‘high’ when exceeding the 75th percentile. Follow‐ups were performed at discharge and 3 months after onset. A poor outcome was defined as a modified Rankin scale (mRS) ≥3. Results A total of 192 patients were included in this study. The median NLR was 3.0 (interquartile range [IQR]: 2.0–3.9). Fifty‐one patients (26.6%) had a high NLR (≥3.9) on admission. Forty‐one patients (21.4%) had a poor outcome at discharge, while 34 patients (17.7%) had a poor outcome at 3 months. Patients with a poor outcome at discharge, and at 3 months after onset, were more likely to have a high NLR at discharge (42.9% vs. 21.9%; p = .005) and at 3 months (44.1% vs. 22.8%; p = .011), compared with those with a better outcome. After adjustment for NIHSS score on admission, ipsilateral severe intracranial large artery occlusion, and atrial fibrillation, logistic regression analyses revealed that a high NLR was a significant predictor of poor outcome at discharge and at 3 months after onset. Conclusions A high NLR on admission could be a useful marker for predicting poor short‐term outcome in patients with mild AIS following IVT., To the best of our knowledge, few studies have focused on the specific relationship between neutrophil‐to‐lymphocyte ratio (NLR) and the short‐term prognosis of patients with mild acute ischemic stroke (AIS) and treated with intravenous thrombolysis (IVT). Our study evaluate whether an increased NLR was predictive of a poor short‐term outcome in patients suffering from mild AIS and treated with IVT. A high NLR (≥3.9) was associated with a poor outcome in patients with mild AIS treated with IVT, at both discharge and 3 months after onset.

Brain age prediction from brain MRI scans not only helps improve brain ageing modelling generally, but also provides benchmarks for predictive analysis methods. Brain-age delta, which is the difference between a subject’s predicted age and true age, has become a meaningful biomarker for the health of the brain. Here, we report the details of our brain age prediction models and results in the Predictive Analysis Challenge 2019. The aim of the challenge was to use T1-weighted brain MRIs to predict a subject’s age in multicentre datasets. We apply a lightweight deep convolutional neural network architecture, Simple Fully Convolutional Neural Network (SFCN), and combined several techniques including data augmentation, transfer learning, model ensemble, and bias correction for brain age prediction. The model achieved first places in both of the two objectives in the PAC 2019 brain age prediction challenge: Mean absolute error (MAE) = 2.90 years without bias removal, and MAE = 2.95 years with bias removal.

A new master-and-slave resonant tank switch approach is proposed to realize narrow switching frequency range and whole range zero voltage switching (ZVS) for series-parallel resonant converter (LCC) with wide operation range. A systematic switch strategy employing paralleled series capacitor (C s ) tanks is fully explored. A master resonant tank is firstly derived based on converter actual operation range. A series of slave resonant tanks are derived using geometric progressions, as 1/2i. The voltage gain is divided into different pieces and different resonant tanks are employed. The switching frequency range maintained similar for each segments. A 5kW SiC LCC converter is built to demonstrate the proposed concept. Three resonant tanks with C s of 5nF, 10nF and 20nF are adopted respectively. With single resonant tank of C s equaling to 20nF, switching frequency need to be adjusted from 280 kHz to 470 kHz for gain range from 0.3-1.05. With the proposed master-and-slave tank switch technique, switching range is shrink to the 390 kHz to 470 kHz for the same gain range by adopting two slave tanks. A 58% reduction of frequency range is achieved.

Short wavelength automated perimetry (SWAP) is known for detecting the early reduction of retinal sensitivity (RS) in glaucoma. It’s application in retinal diseases have also been discussed previously. We investigated the difference in RS measured between standard white-on-white automated perimetry (WW) and blue-on-yellow SWAP in central serous chorioretinopathy (CSC). The overall RS (W-RS, S-RS) as well as the RS inside and outside of the serous retinal detachment (SRD) region were investigated in 26 eyes of 26 CSC patients using WW and SWAP. The central retinal thickness, central choroidal thickness, SRD area (SRDa), and SRD height at the fovea were measured using optic coherence tomography. RS inside the SRD region was lower than that of outside for both perimetries (both p

Launching ultrashort femtosecond photoacoustic pulses with multi-terahertz bandwidth will find broad applications from fundamental acoustics in 2D materials and THz-acoustic and phonon spectroscopy to nondestructive detection in opaque materials with a sub-nanometer resolution. Here we report the generation of ultra-short 344 fs photoacoustic pulses with a 2.1 THz bandwidth from interfacial two-dimensional electron gas using optical femtosecond excitation. A comparison with simulation supports the dominant contribution of hot electron pressure and the ultrafast electron relaxation to produce pulsewidth shorter than the acoustic transit time across the electron wavefunction. Our simulation further indicates the possibility to generate

Diagnosis of intraocular lymphoma (IOL) is usually achieved by histopathological analysis. However, it may lead to inconclusive results due to the scarcity of malignant cells obtained by biopsy, hence leading to delayed diagnosis. We report two cases of IOL with pseudo-hypopyon, a rare feature of IOL, as their initial ocular feature, diagnosed using a multidisciplinary diagnostic approach. Common clinical features of IOL with pseudo-hypopyon were also investigated.Retrospective case series and literature review.Two cases of IOL, a 78-year-old female and a 59-year-old male, whom had been diagnosed with systemic B-cell lymphoma developed pseudo-hypopyon and visual impairment during the course of their chemotherapy. Diagnosis of IOL was achieved from anterior chamber aspiration samples with supplementary diagnostic tools including flow cytometric immunophenotyping, interleukin and IgH gene rearrangement analysis in addition to the conventional histopathological analysis. Generally, pseudo-hypopyon was more commonly seen in secondary IOL and may associate with hyphema and high intraocular pressure.Pseudo-hypopyon is a rare feature of IOL, more commonly seen in secondary IOL, which can be accompanied by hyphema and high intraocular pressure. Supplementary diagnostic tools such as flow cytometric immunophenotyping, interleukin analysis, and immunogloblin H gene rearrangement analysis are useful for supporting the diagnosis of IOL with pseudo-hypopyon.

Conventional resonant gate driver suffers from significant reverse recovery loss due to the usage of Si devices, especially at high frequencies. A novel hybrid resonant gate driver is proposed in this design composed by two hybrid GaN HEMT and Schottky diode half bridges. The hybrid topology merges the merits of efficient resonant turn on and ultra-fast turn off by GaN. The GaN based hybrid resonant-clamping gate driver achieves 29% reduction in gate driver active area. It also has 49.3% reduction in power loss is achieved compared with Si full bridge resonant gate driver.

A PCB integrated GaN gate driver module is proposed to realize fast driving and protection with highly concise system architecture. The PCB based air-coil coupled inductor is adopted as current sensor for ultra-large bandwidth and very compact size. The over-current protection approach proposed in this paper contains only three function blocks enabling very fast response. Low voltage GaN power transistors are used in gate driver circuit. The proposed driver module has the advantages of high speed, prompted response, and low driver loss. This module can also be further integrated with power switch on the same substrate.

The big data characteristics of Marine High-Definition Remote Sensing (MHDRS) has result in the obstacle of the real-time processing, effective decision-making and low efficiency information collection. Aiming at this problem, this paper analyzes the visualization and control integrate system, and establishes a visually analytic system to process the different source of Remote Sensing (RS) data as well as its storage based on the MHDRS data. The result shows that the new method enhances the analysis and sharing with high efficiency.

When the Agile Earth Observation Satellite(AEOS) observes ground target points, the properties of the ground target points often change, which requires the satellite to effectively re-plan its mission in a short time. In order to solve the problem of mission re-planning of the AEOS, an improved genetic algorithm is proposed in this paper. Firstly, the fitness function to be optimized is established according to the satellite's constraints. The benefits of the satellite observation, the constraints of the satellite and the invariant target points included in the re-planned observation sequence is considered in this fitness function. These constraints mainly include time constraints, energy constraints, satellite orbital dynamic constraints, and so on. Secondly, considering the problems faced in the mission re-planning process, such as the satellite's need to complete the mission re-planning in a short time, and the constraints it faces, etc., the Adaptive Mutation Genetic Algorithm(AMGA) is proposed in this paper. Finally, simulation experiments verify that AMGA can complete mission re-planning while meeting various constraints, and that AMGA meets the fast and accurate requirements for solving mission re-planning problems.

Angiotensin converting enzyme 2 (ACE2) plays an important role in inflammation, which is attributable at least, in part, to the conversion of the pro‐inflammatory angiotensin (Ang) II peptide into angiotensin 1‐7 (Ang 1‐7), a peptide which opposes the actions of AngII. ACE2 and AngII are present in many tissues but information on the cornea is lacking. We observed that mice deficient in the Ace2 gene (Ace2−/−), developed a cloudy cornea phenotype as they aged. Haze occupied the central cornea, accompanied by corneal edema and neovascularization. In severe cases with marked chronic inflammation, a cell‐fate switch from a transparent corneal epithelium to a keratinized, stratified squamous, psoriasiform‐like epidermis was observed. The stroma contained a large number of CD11c, CD68, and CD3 positive cells. Corneal epithelial debridement experiments in young ACE2‐deficient mice showed normal appearing corneas, devoid of haze. We hypothesized, however, that these mice are “primed” for a corneal inflammatory response, which once initiated, would persist. In vitro studies reveal that interleukins (IL‐1a, IL‐1b), chemokines (CCL2, CXCL8), and TNF‐α, are all significantly elevated, resulting in a cytokine storm‐like phenotype. This phenotype could be partially rescued by treatment with the AngII type 1 receptor (AT1R) antagonist, losartan, suggesting that the observed effect was mediated by AngII acting on its main receptor. Since the severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) utilizes human ACE2 as the receptor for entry with subsequent downregulation of ACE2, corneal inflammation in Ace2−/− mice may have a similar mechanism with that in COVID‐19 patients. Thus the Ace2−/− cornea, because of easy accessibility, may provide an attractive model to explore the molecular mechanisms, immunological changes, and treatment modalities in patients with COVID‐19.

A compact and efficient self-powered micro-power system, composing of energy harvesting unit and electric power conversion unit is the most promising candidate to support widely distributed information equipment to overcome the constraints of wired and portable power supply. However, current works fail to provide an integrated and optimized system, which suffer from large attenuation loss. Thus, the output power is too micro for board applications with unsatisfied efficiency. To overcome those problems, this paper proposes a novel PCB integrated self-powered micro-electric generator for vehicle engine vibration harvesting. The generator windings and power conversion unit are implemented on same PCB substrate. The micro-generator has the output of ± 2341.85mV AC at 52.3Hz. An all GaN high frequency dual-boost AC-DC converter with boundary conduction mode is employed with impedance matching for maximum power transferring. It also utilizes the output inductance of micro-generator as boost inductor and sensing inductor. The peak output efficiency of the converter reaches to 83% at 3.3V/21.35mW output, which is much higher than state-of-art.

Resonant gate drive (RGD) is the more efficient solution to drive SiC MOSFETs at high switching frequencies with effective gate driver energy saving. It adjusts driving characteristics from RC step response to RLC resonant response at the risk of reduced power transistors’ switching speed and increased switching loss. Resonant inductor becomes the most important component in RGD design and is mutually restraint for gate driver loss reduction and power transistor switching characteristics improvement. Current studies on RGD vaguely uses MOSFET input capacitor (Ciss) from datasheet or total gate charge (Qg) to analyze driver characteristics. The non-linear feature brought by MOSFET miller capacitor is completely ignored, which leads to un-optimized resonant inductor selection and poor understanding in RGD influence on MOSFET switching behaviors. To overcome these issues, a novel time segmented methodology is proposed to provide comprehensive analysis of RGD and understand its impacts on different aspects. The driving loss and SiC switching speed co-optimized series resonant gate driver is demonstrated with 25.5% saving on gate driver loss and 44.4% improvement in driving speed at 200 kHz switching frequency.

Numerous studies have proposed the transplantation of mesenchymal stem cells (MSCs) in the treatment of typical type 2 diabetes mellitus (T2DM). We aimed to find a new strategy with MSC therapy at an early stage of T2DM to efficiently prevent the progressive deterioration of organic dysfunction. Using the high-fat-fed hyperinsulinemia rat model, we found that before the onset of typical T2DM, bone marrow-derived MSCs (BM-MSCs) significantly attenuated rising insulin with decline in glucose as well as restored lipometabolic disorder and liver dysfunction. BM-MSCs also favored the histological structure recovery and proliferative capacity of pancreatic islet cells. More importantly, BM-MSC administration successfully reversed the abnormal expression of insulin resistance-related proteins including GLUT4, phosphorylated insulin receptor substrate 1, and protein kinase Akt and proinflammatory cytokines IL-6 and TNFα in liver. These findings suggested that MSCs transplantation during hyperinsulinemia could prevent most potential risks of T2DM for patients.

Background and purposeEarly neurological deterioration (END) is a common feature in patients with acute ischaemic stroke (AIS) receiving thrombolysis. This study aimed to investigate whether the presence of multiple hypointense vessels (MHVs) on susceptibility-weighted imaging (SWI) could predict END in patients with the anterior circulation AIS treated with recombinant tissue plasminogen activator (r-tPA).MethodsThis was a retrospective study focusing on AIS patients suffering from symptomatic stenosis or occlusion of the middle cerebral artery or internal carotid artery with r-tPA treatment. We collected clinical variables and initial haematological and neuroimaging findings. MHVs were measured on SWI performed after intravenous thrombosis and were defined as the presence of a greater number of veins or veins of a larger diameter with greater signal loss on SWI than those of the contralesional haemisphere. The degree of hyperintensity of MHVs was classified into four grades: none, subtle, moderate and extensive. END was defined as an increase in the National Institutes of Health Stroke Scale score by 2 points during the first 48 hours after the onset of symptoms. Multivariate logistic regressions were conducted to investigate the predictors of END.ResultsThe study included 61 patients (51 males and 10 females) with a mean age of 62.4±12.6 years. Thirty-five (57.4%) patients presented with MHVs: 8 (13.1%) were graded as subtle MHVs, while 23 (37.7%) and 4 (6.6%) were graded as moderate or extensive MHVs, respectively. Twenty patients (32.8%) presented with END. Logistic regression analysis showed that compared with patients without MHVs, moderate MHVs (adjusted OR 5.446, 95% CI 1.360 to 21.800; p=0.017) and extensive MHVs (adjusted OR 15.240, 95% CI 1.200 to 193.544; p=0.036) were significantly associated with END.ConclusionsMHVs might be a useful predictor of END in AIS patients with symptomatic large artery stenosis or occlusion after r-tPA treatment.

Background. Visceral hypersensitivity is a common occurrence of gastrointestinal diseases such as irritable bowel syndrome (IBS), wherein early-life stress (ELS) may have a high predisposition to the development of visceral hypersensitivity in adulthood, with the specific underlying mechanism still elusive. Herein, we assessed the potential effect of small-conductance calcium-activated potassium channel subtype 2 (SK2) in the spinal dorsal horn (DH) on the pathogenesis of visceral hypersensitivity induced by maternal separation (MS) in mice. Methods. Neonatal mice were subjected to the MS paradigm, an established ELS model. In adulthood, the visceral pain threshold and the abdominal withdrawal reflex (AWR) were measured with an inflatable balloon. The elevated plus maze, open field test, sucrose preference test, and forced swim test were employed to evaluate the anxiety- and depression-like behaviors. The expression levels of SK2 in the spinal DH were determined by immunofluorescence and western blotting. The mRNA of SK2 and membrane palmitoylated protein 2 (MPP2) were determined by quantitative real-time polymerase chain reaction (qRT-PCR). Electrophysiology was applied to evaluate the neuronal firing rates and SK2 channel-mediated afterhyperpolarization current (IAHP). The interaction between MPP2 and SK2 was validated by coimmunoprecipitation. Results. In contrast to the naïve mice, ethological findings in MS mice revealed lowered visceral pain threshold, more evident anxiety- and depression-like behaviors, and downregulated expression of membrane SK2 protein and MPP2 protein. Moreover, electrophysiological results indicated increased neuronal firing rates and decreased IAHP in the spinal DH neurons. Nonetheless, intrathecal injection of the SK2 channel activator 1-ethyl-2-benzimidazolinone (1-EBIO) in MS mice could reverse the electrophysiological alterations and elevate the visceral pain threshold. In the naïve mice, administration of the SK2 channel blocker apamin abated IAHP and elevated spontaneous neuronal firing rates in the spinal DH neurons, reducing the visceral pain threshold. Finally, disruption of the MPP2 expression by small interfering RNA (siRNA) could amplify visceral hypersensitivity in naïve mice. Conclusions. ELS-induced visceral pain and visceral hypersensitivity are associated with the underfunction of SK2 channels in the spinal DH.

Human action recognition is an important topic in artificial intelligence with a wide range of applications including surveillance systems, search-and-rescue operations, human-computer interaction, etc. However, most of the current action recognition systems utilize videos captured by stationary cameras. Another emerging technology is the use of unmanned ground and aerial vehicles (UAV/UGV) for different tasks such as transportation, traffic control, border patrolling, wild-life monitoring, etc. This technology has become more popular in recent years due to its affordability, high maneuverability, and limited human interventions. However, there does not exist an efficient action recognition algorithm for UAV-based monitoring platforms. This paper considers UAV-based video action recognition by addressing the key issues of aerial imaging systems such as camera motion and vibration, low resolution, and tiny human size. In particular, we propose an automated deep learning-based action recognition system which includes the three stages of video stabilization using the SURF feature selection and Lucas-Kanade method, human action area detection using faster region-based convolutional neural networks (R-CNN), and action recognition. We propose a novel structure that extends and modifies the InceptionResNet-v2 architecture by combining a 3D CNN architecture and a residual network for action recognition. We achieve an average accuracy of 85.83% for the entire-video-level recognition when applying our algorithm to the popular UCF-ARG aerial imaging dataset. This accuracy significantly improves upon the state-of-the-art accuracy by a margin of 17%.

Background. The relationship between the neutrophil-to-lymphocyte ratio (NLR) and hemorrhagic transformation (HT) in acute ischemic stroke (AIS) treated with intravenous thrombolysis (IVT) remains unclear. This study assessed whether high NLR is associated with HT in this population. Methods. Data were prospectively collected for continuous patients with AIS treated with IVT and retrospectively analyzed. Clinical variables included age, sex, vascular risk factors, National Institutes of Health Stroke Scale (NIHSS) score, onset-to-treatment time, and initial hematologic and neuroimaging findings. HT was confirmed by imaging performed within 3 days after IVT. Symptomatic HT (sHT) was defined as NIHSS score increased by 4 points compared with that on admission according to previously published criteria. The NLR value was based on the blood examination before IVT, and high NLR was defined as ≥75th percentile. Results. The study included 285 patients (201 (70.5%) males, the mean age was 62.3 years (range 29–89)). Seventy-two (25.3%) patients presented with HT, including three (1.1%) with sHT. The median NLR was 2.700 (1.820–4.255, interquartile range). Seventy-one (24.9%) patients had a high NLR (≥4.255) on admission. Univariate analysis indicated that patients with HT had higher NIHSS scores (P<0.001), systolic blood pressure (SBP), platelet counts, lymphocyte counts, and NLR (P<0.05), as well as a greater prevalence of high NLR than those without HT (37.5% vs. 20.7% and P=0.004). Patients with HT were more likely to have hypertension and AF. As lymphocyte counts and high NLR were highly correlated, we used two logistic regression models. In model 1 (with high NLR), NIHSS score on admission (odds ratio (OR) = 1.110, 95% confidence interval (CI) = 1.015–1.044, and P=0.001), AF (OR = 3.986, 95% CI = 2.095–7.585, and P<0.001), and high NLR (OR = 2.078, 95% CI = 1.078–4.003, P=0.029, sensitivity 0.375, and specificity 0.793) were significant predictors of HT. In model 2 (with lymphocyte counts), NIHSS score on admission (OR = 1.111, 95% CI = 1.050–1.175, and P<0.001), AF (OR = 3.853, 95% CI = 2.048–7.248, and P<0.001), and lymphocyte counts (OR = 0.522, 95% CI = 0.333–0.819, and P=0.005) were significantly associated with HT. Conclusions. High NLR could be a useful marker for predicting HT in AIS patients after IVT.

Cloud computing is a type of Internet-based computing that provides shared computing resources and data on demand. To support the massive cloud services, a data center is built with thousands of servers and switches connected by a communication network called a data center network (DCN). Along with the development of virtualization, the data center manager conducts virtual machine (VM) resizing and live migrations to adjust the allocation of VMs and improve the server utilization. However, compared to VM resizing, live migrations can negatively impact the performance of the system depending on the amount of transferred data and the path length. In this paper, we propose an online resource allocation algorithm using VM consolidation to achieve energy efficiency and reduce service-level agreement (SLA) violations of data centers while considering the power usage of servers, the number of migrations, and the path length of migrations in DCNs. Compared to the state-of-the-art mechanism, the proposed algorithm successfully reduces the power consumption, the number of migrations, and the path length of migrations for a dynamic cloud service.

Pulse generator in an ultrasound system produces electrical pulsing signals to drive piezoelectric transducer, which causes mechanical vibration of the crystals and generates sound waves. Different from conventional imaging short pulses, high-power ultrasonic system for therapeutic applications requires MHz pulses bursts of up to tens of milliseconds. The capability of switching high voltage (±90 V) at multi-MHz, delivering effective power efficiently, is crucial for practical systems. The advantages of low device loss at high switching frequency, and high power density make gallium nitride (GaN) high electron mobility transistors better devices than traditional silicon (Si) MOSFETs in such system. The GaN-based high-frequency transformer push–pull inverter presented in this paper is capable to produce high energy pulsating output with burst pulse length up to 50 ms and bipolar pulse amplitude of 180 Vpp. The maximum pulse frequency can be up to 10 MHz. The peak output power is 90 W with power density of 50.85 W/in2. The peak power for all the 128 pulser channels reaches up to 11.5 KW with average power of 192 W. This is the highest output power for pulse drivers that have been reported. A novel power transistor based RF switch circuit is also proposed in this design as the interface between image signal, high power signal, and return signal.