DeepFacePencil: Creating Face Images from Freehand Sketches

In this paper, we explore the task of generating photo-realistic face images from hand-drawn sketches. Existing image-to-image translation methods require a large-scale dataset of paired sketches and images for supervision. They typically utilize synthesized edge maps of face images as training data. However, these synthesized edge maps strictly align with the edges of the corresponding face images, which limit their generalization ability to real hand-drawn sketches with vast stroke diversity. To address this problem, we propose DeepFacePencil, an effective tool that is able to generate photo-realistic face images from hand-drawn sketches, based on a novel dual generator image translation network during training. A novel spatial attention pooling (SAP) is designed to adaptively handle stroke distortions which are spatially varying to support various stroke styles and different levels of details. We conduct extensive experiments and the results demonstrate the superiority of our model over existing methods on both image quality and model generalization to hand-drawn sketches.Comment: ACM MM 2020 (oral

Validation of the Chinese version of the "Mood Disorder Questionnaire" for screening bipolar disorder among patients with a current depressive episode

<p>Abstract</p> <p>Background</p> <p>The Mood Disorder Questionnaire (MDQ) is a well-recognized screening tool for bipolar disorder, but its Chinese version needs further validation. This study aims to measure the accuracy of the Chinese version of the MDQ as a screening instrument for bipolar disorder (BPD) in a group of patients with a current major depressive episode.</p> <p>Methods</p> <p>142 consecutive patients with an initial DSM-IV-TR diagnosis of a major depressive episode were screened for BPD using the Chinese translation of the MDQ and followed up for one year. The final diagnosis, determined by a special committee consisting of three trained senior psychiatrists, was used as a 'gold standard' and ROC was plotted to evaluate the performance of the MDQ. The optimal cut-off was chosen by maximizing the Younden's index.</p> <p>Results</p> <p>Of the 142 patients, 122 (85.9%) finished the one year follow-up. On the basis of a semi-structured clinical interview 48.4% (59/122) received a diagnosis of unipolar depression (UPD), 36.9% (45/122) BPDII and 14.8% (18/122) BPDI. At the end of the one year follow-up,9 moved from UPD to BPD, 2 from BPDII to UPD, 1 from BPDII to BPDI, the overall rate of initial misdiagnosis was 16.4%. MDQ showed a good accuracy for BPD: the optimal cut-off was 4, with a sensitivity of 0.72 and a specificity of 0.73. When BPDII and BPDI were calculated independently, the optimal cut-off for BPDII was 4, with a sensitivity of 0.70 and a specificity of 0.73; while the optimal cut-off for BPDI was 5, with a sensitivity of 0.67 and a specificity of 0.86.</p> <p>Conclusions</p> <p>Our results show that the Chinese version of MDQ is a valid tool for screening BPD in a group of patients with current depressive episode on the Chinese mainland.</p

The correlation between metabolic syndrome and neurocognitive and social cognitive performance of patients with schizophrenia

Cognitive impairment is one of the core symptoms of schizophrenia, and patients with schizophrenia are at increased risk of metabolic syndrome (MS). However, the role of MS in cognitive impairment of schizophrenia is not established. This study investigated the correlation between neurocognitive, social cognitive performance and MS with schizophrenia. One hundred and fifty eight (158) schizophrenia patients were divided into 3 groups with ① normal metabolism, ② metabolic disorder (only meeting 1 or 2 MS criteria), and ③ metabolic syndrome (meeting 3 or more MS criteria). MATRICS Consensus Cognitive Battery)MCCB(and the Brief Psychiatric Rating Scale)BPRS(were used to evaluate cognitive performance and clinical symptoms. Blood samples were obtained to detect glucose and lipid metabolic levels. Overall MCCB and subscale T scores in the normal metabolism and metabolic disorder groups were better than in the MS group. After controlling for the confounding factors including age, sex, the usage of hypolipidemic and hypoglycemic drugs, and disease duration, metabolic deficits had effects on the symbol coding and spatial span scores. The results suggest that a defective metabolic state might play a role in neurocognitive performance of schizophrenia patients

The Cauchy problem for the liquid crystals system in the critical Besov space with negative index

summary:The local well-posedness for the Cauchy problem of the liquid crystals system in the critical Besov space $\dot {B}_{p,1}^{n/p-1}(\mathbb R^n)\times \dot {B}_{p,1}^{n/p}(\mathbb R^n)$ with $n<p<2n$ is established by using the heat semigroup theory and the Littlewood-Paley theory. The global well-posedness for the system is obtained with small initial datum by using the fixed point theorem. The blow-up results for strong solutions to the system are also analysed

Changes in composition, cellulose degradability and biochemical methane potential of Miscanthus species during the growing season

The composition, cellulose degradability and biochemical methane potential (BMP) of M. sinensis, M. floridulus, Miscanthus x giganteus and M. lutarioriparius were investigated concomitantly at different growth/ harvest times during their growing season. For all the four species, there was only a slight change in the compositional content. Meanwhile there was a huge change in the BMP values. At the growth time of 60 days the BMPs ranged from 247.1 to 266.5 ml g(-1) VS. As growth time was prolonged, the BMPs decreased by 11-35%. For each species, the BMP was positively correlated to the cellulose degradability with the correlation coefficients (R-2) ranging from 0.8055 to 0.9925. This suggests that besides the biomass yield, it is justifiable to consider cellulose degradability when selecting the suitable harvest time for biofuels production from Miscanthus, especially in tropical and subtropical regions where Miscanthus can be harvested twice or more within a year. (C) 2017 Elsevier Ltd. All rights reserved.</p

A Mission Reliability-Driven Manufacturing System Health State Evaluation Method Based on Fusion of Operational Data

The rapid development of complexity and intelligence in manufacturing systems leads to an increase in potential operational risks and therefore requires a more comprehensive system-level health diagnostics approach. Based on the massive multi-source operational data collected by smart sensors, this paper proposes a mission reliability-driven manufacturing system health state evaluation method. Characteristic attributes affecting the mission reliability are monitored and analyzed based on different sensor groups, including the performance state of the manufacturing equipment, the execution state of the production task and the quality state of the manufactured product. The Dempster-Shafer (D-S) evidence theory approach is used to diagnose the health state of the manufacturing system. Results of a case study show that the proposed evaluation method can dynamically and effectively characterize the actual health state of manufacturing systems