Zhaoogden0684

Throughout their evolutionary history, humans have tried to domesticate a variety of wild terrestrial mammals, resulting in a limited number that has been successfully domesticated. Among these domesticated species, domestic goats (Capra aegagrus hircus) are a useful model species to study the effects of ontogenesis on the socio-cognitive abilities of domestic non-companion animals in their interactions with humans. To this end, the behavioral responses of two groups of goats with a different background of human socialization (high and low socialization) were compared in the impossible task test, an experimental paradigm aimed to study socio-cognitive skills and the tendency to interact with humans. Our results show that, when the task became impossible to solve, goats with a higher level of socialization interacted with the experimenter for a greater amount of time than subjects in the low socialization group, whereas the latter group exhibited increased door directed behavior. Overall, highly socialized goats made more social contact with humans compared to the other group in the impossible task paradigm.OBJECTIVES The aim of this study is to provide information about prevalence, etiology, risk factors, clinical characteristics and endoscopic features of various types of infectious esophagitis in children. METHODS We performed a total of 520 upper gastrointestinal tract endoscopies in Pediatric Clinic II, Emergency Hospital for Children, Cluj-Napoca. Indications for endoscopy in our cohort were gastrointestinal tract symptoms such as dysphagia, heartburn, or appetite loss. RESULTS The prevalence of infectious esophagitis in the study population was 2.11% (11 patients). Candida albicans (C. albicans) was the most frequent cause. Our data illustrates that herpes simplex virus (HSV)-induced esophagitis is common in immunocompromised patients and should be systematically suspected in cases of severe dysphagia, heartburn, or hematemesis. RG-7112 nmr In the present study, all cytomegalovirus (CMV) esophagitis patients were immunocompromised. Immunodeficiency (81.8%) and prolonged antibiotic therapy with broad-spectrum antibiotics were by far the most important risk factors involved in the pathogenicity of the disease. Dysphagia, appetite loss, heartburn, epigastralgia, and hematemesis were the main clinical manifestations. Infectious esophagitis was associated with significant mortality. In four patients, endoscopy during life showed signs of infectious esophagitis; however, the precise etiology was only established post-mortem, in the pathological anatomy laboratory department. A risk factor involved in pathogenesis of post-mortem diagnosed infectious esophagitis is the DiGeorge syndrome for CMV and HSV patients. CONCLUSIONS The study illustrates that infectious esophagitis should be considered in immunocompromised infants with prolonged antibiotic therapy with broad-spectrum antibiotics.In the past decade, time series data have been generated from various fields at a rapid speed, which offers a huge opportunity for mining valuable knowledge. As a typical task of time series mining, Time Series Classification (TSC) has attracted lots of attention from both researchers and domain experts due to its broad applications ranging from human activity recognition to smart city governance. Specifically, there is an increasing requirement for performing classification tasks on diverse types of time series data in a timely manner without costly hand-crafting feature engineering. Therefore, in this paper, we propose a framework named Edge4TSC that allows time series to be processed in the edge environment, so that the classification results can be instantly returned to the end-users. Meanwhile, to get rid of the costly hand-crafting feature engineering process, deep learning techniques are applied for automatic feature extraction, which shows competitive or even superior performance compared to state-of-the-art TSC solutions. However, because time series presents complex patterns, even deep learning models are not capable of achieving satisfactory classification accuracy, which motivated us to explore new time series representation methods to help classifiers further improve the classification accuracy. In the proposed framework Edge4TSC, by building the binary distribution tree, a new time series representation method was designed for addressing the classification accuracy concern in TSC tasks. By conducting comprehensive experiments on six challenging time series datasets in the edge environment, the potential of the proposed framework for its generalization ability and classification accuracy improvement is firmly validated with a number of helpful insights.Aiming at addressing the issues related to the tuning of loop closure detection parameters for indoor 2D graph-based simultaneous localization and mapping (SLAM), this article proposes a multi-objective optimization method for these parameters. The proposed method unifies the Karto SLAM algorithm, an efficient evaluation approach for map quality with three quantitative metrics, and a multi-objective optimization algorithm. More particularly, the evaluation metrics, i.e., the proportion of occupied grids, the number of corners and the amount of enclosed areas, can reflect the errors such as overlaps, blurring and misalignment when mapping nested loops, even in the absence of ground truth. The proposed method has been implemented and validated by testing on four datasets and two real-world environments. For all these tests, the map quality can be improved using the proposed method. Only loop closure detection parameters have been considered in this article, but the proposed evaluation metrics and optimization method have potential applications in the automatic tuning of other SLAM parameters to improve the map quality.The use of complementary medicine has recently increased in an attempt to find effective alternative therapies that reduce the adverse effects of drugs. Punica granatum L. (pomegranate) has been used in traditional medicine for different kinds of pain. This review aims to explore the scientific evidence about the antinociceptive effect of pomegranate. A selection of original scientific articles that accomplished the inclusion criteria was carried out. It was found that different parts of pomegranate showed an antinociceptive effect; this effect can be due mainly by the presence of polyphenols, flavonoids, or fatty acids. It is suggested in the literature that the mechanisms of action may be related to the activation of the L-arginine / NO pathway, members of the TRP superfamily (TRPA1 or TRPV1) and the opioid system. The implications for the field are to know the mechanisms of action by which this effect is generated and thus be able to create alternative treatments for specific types of pain, which help alleviate it and reduce the adverse effects produced by drugs.