End-to-End Photo-Sketch Generation via Fully Convolutional Representation Learning

Sketch-based face recognition is an interesting task in vision and multimedia research, yet it is quite challenging due to the great difference between face photos and sketches. In this paper, we propose a novel approach for photo-sketch generation, aiming to automatically transform face photos into detail-preserving personal sketches. Unlike the traditional models synthesizing sketches based on a dictionary of exemplars, we develop a fully convolutional network to learn the end-to-end photo-sketch mapping. Our approach takes whole face photos as inputs and directly generates the corresponding sketch images with efficient inference and learning, in which the architecture are stacked by only convolutional kernels of very small sizes. To well capture the person identity during the photo-sketch transformation, we define our optimization objective in the form of joint generative-discriminative minimization. In particular, a discriminative regularization term is incorporated into the photo-sketch generation, enhancing the discriminability of the generated person sketches against other individuals. Extensive experiments on several standard benchmarks suggest that our approach outperforms other state-of-the-art methods in both photo-sketch generation and face sketch verification.Comment: 8 pages, 6 figures. Proceeding in ACM International Conference on Multimedia Retrieval (ICMR), 201

Recent Advances in Morphological Cell Image Analysis

This paper summarizes the recent advances in image processing methods for morphological cell analysis. The topic of morphological analysis has received much attention with the increasing demands in both bioinformatics and biomedical applications. Among many factors that affect the diagnosis of a disease, morphological cell analysis and statistics have made great contributions to results and effects for a doctor. Morphological cell analysis finds the cellar shape, cellar regularity, classification, statistics, diagnosis, and so forth. In the last 20 years, about 1000 publications have reported the use of morphological cell analysis in biomedical research. Relevant solutions encompass a rather wide application area, such as cell clumps segmentation, morphological characteristics extraction, 3D reconstruction, abnormal cells identification, and statistical analysis. These reports are summarized in this paper to enable easy referral to suitable methods for practical solutions. Representative contributions and future research trends are also addressed

Emerging Roles of Liquid–Liquid Phase Separation in Cancer: From Protein Aggregation to Immune-Associated Signaling

Liquid–liquid Phase Separation (LLPS) of proteins and nucleic acids has emerged as a new paradigm in the study of cellular activities. It drives the formation of liquid-like condensates containing biomolecules in the absence of membrane structures in living cells. In addition, typical membrane-less condensates such as nuclear speckles, stress granules and cell signaling clusters play important roles in various cellular activities, including regulation of transcription, cellular stress response and signal transduction. Previous studies highlighted the biophysical and biochemical principles underlying the formation of these liquid condensates. The studies also showed how these principles determine the molecular properties, LLPS behavior, and composition of liquid condensates. While the basic rules driving LLPS are continuously being uncovered, their function in cellular activities is still unclear, especially within a pathological context. Therefore, the present review summarizes the recent progress made on the existing roles of LLPS in cancer, including cancer-related signaling pathways, transcription regulation and maintenance of genome stability. Additionally, the review briefly introduces the basic rules of LLPS, and cellular signaling that potentially plays a role in cancer, including pathways relevant to immune responses and autophagy

Pre-anesthetic use of butorphanol for the prevention of emergence agitation in thoracic surgery: A multicenter, randomized controlled trial

BackgroundEmergence agitation (EA) is common in patients after general anesthesia (GA) and is associated with poor outcomes. Patients with thoracic surgery have a higher incidence of EA compared with other surgery. This study aimed to investigate the impact of pre-anesthetic butorphanol infusion on the incidence of EA in patients undergoing thoracic surgery with GA.Materials and methodsThis prospective randomized controlled trial (RCT) was conducted in 20 tertiary hospitals in China. A total of 668 patients undergoing elective video-assisted thoracoscopic lobectomy/segmentectomy for lung cancer were assessed for eligibility, and 620 patients were enrolled. In total, 296 patients who received butorphanol and 306 control patients were included in the intention-to-treat analysis. Patients in the intervention group received butorphanol 0.02 mg/kg 15 min before induction of anesthesia. Patients in the control group received volume-matched normal saline in the same schedule. The primary outcome was the incidence of EA after 5 min of extubation, and EA was evaluated using the Riker Sedation-Agitation Scale (RSAS). The incidence of EA was determined by the chi-square test, with a significance of P < 0.05.ResultsIn total, 296 patients who received butorphanol and 306 control patients were included in the intention-to-treat analysis. The incidence of EA 5 min after extubation was lower with butorphanol treatment: 9.8% (29 of 296) vs. 24.5% (75 of 306) in the control group (P = 0.0001). Patients who received butorphanol had a lower incidence of drug-related complications (including injecting propofol pain and coughing with sufentanil): 112 of 296 vs. 199 of 306 in the control group (P = 0.001) and 3 of 296 vs. 35 of 306 in the control group (P = 0.0001).ConclusionThe pre-anesthetic administration of butorphanol reduced the incidence of EA after thoracic surgery under GA.Clinical trial registration[http://www.chictr.org.cn/showproj.aspx?proj=42684], identifier [ChiCTR1900025705]

The Ninth Visual Object Tracking VOT2021 Challenge Results

acceptedVersionPeer reviewe

Application of Trap Cropping as Companion Plants for the Management of Agricultural Pests: A Review

Companion planting is a well-known strategy to manage insect pests and support a natural enemy population through vegetative diversification. Trap cropping is one such type of special companion planting strategy that is traditionally used for insect pest management through vegetative diversification used to attract insect pests away from the main crops during a critical time period by providing them an alternative preferred choice. Trap crops not only attract the insects for feeding and oviposition, but also act as a sink for any pathogen that may be a vector. Considerable research has been conducted on different trap crops as companion plant species to develop improved pest management strategies. Despite this, little consensus exists regarding optimal trap cropping systems for diverse pest management situations. An advantage of trap cropping over an artificially released natural enemy-based biological control could be an attractive remedy for natural enemies in cropping systems. Besides, many trap crop species can conserve natural enemies. This secondary effect of attracting natural enemies may be an advantage compared to the conventional means of pest control. However, this additional consideration requires a more knowledge-intensive background to designing an effective trap cropping system. We have provided information based on different trap crops as companion plant, their functions and an updated list of trap cropping applications to attract insect pests and natural enemies that should be proven as helpful in future trap cropping endeavors