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As, respectively. Conclusions This study identifies some key and functional coexpression modules involved in IPAH, as well as a potential IPAH-related miRNA-mRNA regulated network. It provides deepening insights into the molecular mechanisms and provides vital clues in seeking novel therapeutic targets for IPAH.Tooth loss reflects the endpoint of two major dental diseases dental caries and periodontitis. These comprise 2% of the global burden of human diseases. A lower number of teeth has been associated with various systemic diseases, in particular, atherosclerotic cardiovascular diseases (ACVD). The aim was to summarize the evidence of tooth loss related to the risk for ACVD or death. Cohort studies with prospective follow-up data were retrieved from Medline-PubMed and EMBASE. Following the PRISMA guidelines, two reviewers independently selected articles, assessed the risk of bias, and extracted data on the number of teeth (tooth loss; exposure) and ACVD-related events and all-cause mortality (ACM) (outcome). A total of 75 articles were included of which 44 were qualified for meta-analysis. A lower number of teeth was related to a higher outcome risk; the pooled risk ratio (RR) for the cumulative incidence of ACVD ranged from 1.69 to 2.93, and for the cumulative incidence of ACM, the RR ranged from 1.76 to 2.27. The pooled multiple adjusted hazard ratio (HR) for the incidence density of ACVD ranged from 1.02 to 1.21, and for the incidence density of ACM, the HR ranged from 1.02 to 1.30. This systematic review and meta-analyses of survival data show that a lower number of teeth is a risk factor for both ACVD and death. Health care professionals should use this information to inform their patients and increase awareness on the importance of good dental health and increase efforts to prevent tooth loss.Background Myocardial perfusion imaging modalities, such as cardiac magnetic resonance (CMR), single-photon emission computed tomography (SPECT), and positron emission tomography (PET), are well-established non-invasive diagnostic methods to detect hemodynamically significant coronary artery disease (CAD). The aim of this meta-analysis is to compare CMR, SPECT, and PET in the diagnosis of CAD and to provide evidence for further research and clinical decision-making. Methods PubMed, Web of Science, EMBASE, and Cochrane Library were searched. Studies that used CMR, SPECT, and/or PET for the diagnosis of CAD were included. Pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio with their respective 95% confidence interval, and the area under the summary receiver operating characteristic (SROC) curve were calculated. Results A total of 203 articles were identified for inclusion in this meta-analysis. The pooled sensitivity values of CMR, SPECT, and PET were 0.86, 0.83, and 0.85, respectively. Their respective overall specificity values were 0.83, 0.77, and 0.86. Results in subgroup analysis of the performance of SPECT with 201Tl showed the highest pooled sensitivity [0.85 (0.82, 0.88)] and specificity [0.80 (0.75, 0.83)]. 99mTc-tetrofosmin had the lowest sensitivity [0.76 (0.67, 0.82)]. In the subgroup analysis of PET tracers, results indicated that 13N had the lowest pooled sensitivity [0.83 (0.74, 0.89)], and the specificity was the highest [0.91 (0.81, 0.96)]. Conclusion Our meta-analysis indicates that CMR and PET present better diagnostic performance for the detection of CAD as compared with SPECT.[This corrects the article DOI 10.3389/frobt.2020.586707.].Biometric security applications have been employed for providing a higher security in several access control systems during the past few years. The handwritten signature is the most widely accepted behavioral biometric trait for authenticating the documents like letters, contracts, wills, MOU's, etc. for validation in day to day life. In this paper, a novel algorithm to detect gender of individuals based on the image of their handwritten signatures is proposed. The proposed work is based on the fusion of textural and statistical features extracted from the signature images. The LBP and HOG features represent the texture. The writer's gender classification is carried out using machine learning techniques. The proposed technique is evaluated on own dataset of 4,790 signatures and realized an encouraging accuracy of 96.17, 98.72 and 100% for k-NN, decision tree and Support Vector Machine classifiers, respectively. The proposed method is expected to be useful in design of efficient computer vision tools for authentication and forensic investigation of documents with handwritten signatures.Modern scenarios in robotics involve human-robot collaboration or robot-robot cooperation in unstructured environments. In human-robot collaboration, the objective is to relieve humans from repetitive and wearing tasks. This is the case of a retail store, where the robot could help a clerk to refill a shelf or an elderly customer to pick an item from an uncomfortable location. In robot-robot cooperation, automated logistics scenarios, such as warehouses, distribution centers and supermarkets, often require repetitive and sequential pick and place tasks that can be executed more efficiently by exchanging objects between robots, provided that they are endowed with object handover ability. Use of a robot for passing objects is justified only if the handover operation is sufficiently intuitive for the involved humans, fluid and natural, with a speed comparable to that typical of a human-human object exchange. The approach proposed in this paper strongly relies on visual and haptic perception combined with suitable algorithms for controlling both robot motion, to allow the robot to adapt to human behavior, and grip force, to ensure a safe handover. The control strategy combines model-based reactive control methods with an event-driven state machine encoding a human-inspired behavior during a handover task, which involves both linear and torsional loads, without requiring explicit learning from human demonstration. Selleckchem Epibrassinolide Experiments in a supermarket-like environment with humans and robots communicating only through haptic cues demonstrate the relevance of force/tactile feedback in accomplishing handover operations in a collaborative task.