Fused Text Segmentation Networks for Multi-oriented Scene Text Detection

In this paper, we introduce a novel end-end framework for multi-oriented scene text detection from an instance-aware semantic segmentation perspective. We present Fused Text Segmentation Networks, which combine multi-level features during the feature extracting as text instance may rely on finer feature expression compared to general objects. It detects and segments the text instance jointly and simultaneously, leveraging merits from both semantic segmentation task and region proposal based object detection task. Not involving any extra pipelines, our approach surpasses the current state of the art on multi-oriented scene text detection benchmarks: ICDAR2015 Incidental Scene Text and MSRA-TD500 reaching Hmean 84.1% and 82.0% respectively. Morever, we report a baseline on total-text containing curved text which suggests effectiveness of the proposed approach.Comment: Accepted by ICPR201

Neural basis of dysphagia in stroke: A systematic review and meta-analysis

ObjectivesDysphagia is a major cause of stroke infection and death, and identification of structural and functional brain area changes associated with post-stroke dysphagia (PSD) can help in early screening and clinical intervention. Studies on PSD have reported numerous structural lesions and functional abnormalities in brain regions, and a systematic review is lacking. We aimed to integrate several neuroimaging studies to summarize the empirical evidence of neurological changes leading to PSD.MethodsWe conducted a systematic review of studies that used structural neuroimaging and functional neuroimaging approaches to explore structural and functional brain regions associated with swallowing after stroke, with additional evidence using a live activation likelihood estimation (ALE) approach.ResultsA total of 35 studies were included, including 20 studies with structural neuroimaging analysis, 14 studies with functional neuroimaging analysis and one study reporting results for both. The overall results suggest that structural lesions and functional abnormalities in the sensorimotor cortex, insula, cerebellum, cingulate gyrus, thalamus, basal ganglia, and associated white matter connections in individuals with stroke may contribute to dysphagia, and the ALE analysis provides additional evidence for structural lesions in the right lentiform nucleus and right thalamus and functional abnormalities in the left thalamus.ConclusionOur findings suggest that PSD is associated with neurological changes in brain regions such as sensorimotor cortex, insula, cerebellum, cingulate gyrus, thalamus, basal ganglia, and associated white matter connections. Adequate understanding of the mechanisms of neural changes in the post-stroke swallowing network may assist in clinical diagnosis and provide ideas for the development of new interventions in clinical practice

Comparison of different momentum control variables on assimilating radar observations for the forecasts of a dispersive convective event

In this study, the effects of background error covariance (BE) using the stream function ψ and unbalanced velocity potential χu as momentum control variables (CV5 scheme) and BE using the velocity U and V as momentum control variables (CV7 scheme) on assimilating radar radial velocity and reflectivity data for short-term forecasts of dispersive convection in a weak environmental field are explored based on the weather research and forecasting model (WRF) model and its 3DVAR assimilation system. The 4 km resolution forecast samples are generated to formulate the CV5 and CV7 BE by the National Meteorological Center (NMC) method. The single-observation experiments reveal that the differences between the two BE statistics are mainly reflected on the momentum control variables. The increment of wind field from CV7 shows more small-scale local characteristics. Comparing with control experiment, real radar observation assimilation tests of CV5 and CV7 both improve the reflectivity and precipitation forecasts. But the CV7 scheme improves the forecasting of strong convective systems in weak environmental fields better than CV5. First, the CV7 scheme improves both reflectivity and dispersive precipitation forecasts and significantly suppresses the spurious precipitation forecasts when compared with the CV5 scheme. In addition, CV7 also significantly reduces the forecast errors of surface variables and the wind analysis from CV7 is more local. Further analysis shows that the CV7 improves the water vapor convergence conditions compared to the CV5 scheme, which may be the reason for its better performance in the subsequent forecasts

The progression rate of spinocerebellar ataxia type 3 varies with disease stage

Background: In polyglutamine (polyQ) diseases, the identification of modifiers and the construction of prediction model for progression facilitate genetic counseling, clinical management and therapeutic interventions. Methods: Data were derived from the longest longitudinal study, with 642 examinations by International Cooperative Ataxia Rating Scale (ICARS) from 82 SCA3 participants. Using different time scales of disease duration, we performed multiple different linear, quadratic and piece-wise linear growth models to fit the relationship between ICARS scores and duration. Models comparison was employed to determine the best-fitting model according to goodness-of-fit tests, and the analysis of variance among nested models. Results: An acceleration was detected after 13 years of duration: ICARS scores progressed 2.445 (SE: 0.185) points/year before and 3.547 (SE: 0.312) points/year after this deadline. Piece-wise growth model fitted better to studied data than other two types of models. The length of expanded CAG repeat (CAGexp) in ATXN3 gene significantly influenced progression. Age at onset of gait ataxia (AOga), a proxy for aging process, was not an independent modifier but affected the correlation between CAGexp and progression. Additionally, gender had no significant effect on progression rate of ICARS. The piece-wise growth models were determined as the predictive models, and ICARS predictions from related models were available. Conclusions: We first confirmed that ICARS progressed as a nonlinear pattern and varied according to different stages in SCA3. In addition to ATXN3 CAGexp, AOga or aging process regulated the progression by interacting with CAGexp

An analysis of teacher's role as motivator to student's learning motivation in English lesson at SMPN 1 Sedati Sidoarjo

Teacher is one of the important components in the process of learning and teaching to form the potential human resource in developed era. One of the teacher's roles is as motivator. Teacher's role as motivator is important to improve student's motivation in learning. Teacher has to stimulate, motivate and reinforce the students to stick out their potency, activity and creativity. When the writer observed the school, he found the school that has a good motivation. The school is SMPN 1 Sedati Sidoarjo. All of the students were enthusiastic to learn English. The grade of the students was good. Their average grade was eight. It was caused by the motivation that had been given by teacher. From that reason, the writer has two problems of the study. These are: (1) How is teacher's role as motivator done by English teacher and (2) how far students are motivated by teacher. And to answer problem of the study, the researcher used qualitative-descriptive method and used four instruments. These are check list observation, interview, questionnaire, and documentation. The teacher of that school was very innovative in teaching the students. He used the application program that he took when he had training in America. It was suitable to be applied in that school because it was supported by complete facilities because laptop and LCD were available in that school and it was suitable with the school's curriculum. Teacher often invite the students to be participated in the English event. It can be proved by the appreciation of students was very more. The relationship between teacher and students was very close. So the students were very enthusiastic to learn English. The students made the teacher as their inspiration and motivation to learn especially in English because the teacher always shared the important to learn English and anything about life

An improved contrastive learning network for semi-supervised multi-structure segmentation in echocardiography

Cardiac diseases have high mortality rates and are a significant threat to human health. Echocardiography is a commonly used imaging technique to diagnose cardiac diseases because of its portability, non-invasiveness and low cost. Precise segmentation of basic cardiac structures is crucial for cardiologists to efficiently diagnose cardiac diseases, but this task is challenging due to several reasons, such as: (1) low image contrast, (2) incomplete structures of cardiac, and (3) unclear border between the ventricle and the atrium in some echocardiographic images. In this paper, we applied contrastive learning strategy and proposed a semi-supervised method for echocardiographic images segmentation. This proposed method solved the above challenges effectively and made use of unlabeled data to achieve a great performance, which could help doctors improve the accuracy of CVD diagnosis and screening. We evaluated this method on a public dataset (CAMUS), achieving mean Dice Similarity Coefficient (DSC) of 0.898, 0.911, 0.916 with 1/4, 1/2 and full labeled data on two-chamber (2CH) echocardiography images, and of 0.903, 0.921, 0.928 with 1/4, 1/2 and full labeled data on four-chamber (4CH) echocardiography images. Compared with other existing methods, the proposed method had fewer parameters and better performance. The code and models are available at https://github.com/gpgzy/CL-Cardiac-segmentation

2-Deoxyglucose alleviates migraine-related behaviors by modulating microglial inflammatory factors in experimental model of migraine

BackgroundTargeting metabolic pathways has emerged as a new migraine treatment strategy as researchers realize the critical role metabolism plays in migraine. Activated inflammatory cells undergo metabolic reprogramming and rely on glycolysis to function. The objective of this study was to investigate the glycolysis changes in the experimental model of migraine and the effect of glycolysis inhibitor 2-Deoxy-D-glucose (2-DG) in the pathophysiology of migraine.MethodsWe used a rat model of migraine that triggered migraine attacks by applying inflammatory soup (IS) to the dura and examined changes in glycolysis. 2-DG was used to inhibit glycolysis, and the effects of 2-DG on mechanical ectopic pain, microglial cell activation, calcitonin gene-related peptides (CGRP), c-Fos, and inflammatory factors induced by inflammatory soup were observed. LPS stimulated BV2 cells to establish a model in vitro to observe the effects of 2-DG on brain-derived neurotrophic factor (BDNF) after microglia activation.ResultsIn the experimental model of migraine, key enzymes involved in glycolysis such as phosphofructokinase platelet (PFKP), hexokinase (HK2), hypoxia inducible factor-1α (HIF-1α), lactate dehydrogenase (LDH) and pyruvate kinase (PKM2) were expressed in the medullary dorsal horn. While the expression of electronic respiratory transport chain complex IV (COXIV) decreased. There were no significant changes in glucose 6-phosphate dehydrogenase (G6PD), a key enzyme in the pentose phosphate pathway. The glycolysis inhibitor 2-DG alleviated migraine-like symptoms in an experimental model of migraine, reduced the release of proinflammatory cytokines caused by microglia activation, and decreased the expression of CGRP and c-Fos. Further experiments in vitro demonstrated that glycolysis inhibition can reduce the release of Iba-1/proBDNF/BDNF and inhibit the activation of microglia.ConclusionThe migraine rat model showed enhanced glycolysis. This study suggests that glycolytic inhibitor 2-DG is an effective strategy for alleviating migraine-like symptoms. Glycolysis inhibition may be a new target for migraine treatment

Phase diagram of In–Co–Sb system and thermoelectric properties of In-containing skutterudites

In-containing skutterudites have long attracted much attention and debate partly due to the solubility limit issue of indium in CoSb_3. The isothermal section of the equilibrium phase diagram for the In–Co–Sb system at 873 K is proposed using knowledge of the related binary phase diagrams and experimental data, which explains the debated indium solubility that depends on Sb content. In this paper, a series of In-containing skutterudite samples (In_xCo_4Sb_(12−x/3) with x varying from 0.075 to 0.6 and In_(0.3)Co_(4−y)Sb_(11.9+y) with y changing from −0.20 to 0.20) are synthesized and characterized. X-ray analysis and scanning electron microscopy images indicate that, up to x = 0.27, single-phase skutterudites are obtained with lattice constant increasing with In fraction x. A fixed-composition skutterudite In_(0.27±0.01)Co_4Sb_(11.9) was determined for the Co-rich side of In–CoSb_3 which is in coexistence with liquid InSb and CoSb_2. Indium, like Ga, is expected, from DFT calculations, to form compound defects in In-containing skutterudites. However, relatively higher carrier concentrations of In-containing skutterudites compared to Ga-containing skutterudites indicate the existence of not fully charge-compensated compound defects, which can also be explained by DFT calculations. The net n-type carrier concentration that naturally forms from the complex defects is close to the optimum for thermoelectric performance, enabling a maximum zT of 1.2 for the fixed skutterudite composition In_(0.27)Co_4Sb_(11.9) at 750 K