Phase transitions in a holographic s+p model with backreaction

In a previous paper (arXiv:1309.2204, JHEP 1311 (2013) 087), we present a holographic s+p superconductor model with a scalar triplet charged under an SU(2) gauge field in the bulk. We also study the competition and coexistence of the s-wave and p-wave orders in the probe limit. In this work we continue to study the model by considering the full back-reaction The model shows a rich phase structure and various condensate behaviors such as the "n-type" and "u-type" ones, which are also known as reentrant phase transitions in condensed matter physics. The phase transitions to the p-wave phase or s+p coexisting phase become first order in strong back-reaction cases. In these first order phase transitions, the free energy curve always forms a swallow tail shape, in which the unstable s+p solution can also play an important role. The phase diagrams of this model are given in terms of the dimension of the scalar order and the temperature in the cases of eight different values of the back reaction parameter, which show that the region for the s+p coexisting phase is enlarged with a small or medium back reaction parameter, but is reduced in the strong back-reaction cases.Comment: 15 pages(two-column), 9 figure

Analgesic, anti-inflammatory and immuno-modulatory effects of dezocine-propofol anesthesia combination following colonoscopy

Purpose: To study and compare the analgesic, anti-inflammatory and immuno-modulatory effects of dezocine-propofol, and fentanyl-propofol combinations in colonoscopy.Methods: One hundred and thirty-four patients who received painless colonoscopy in Eastern Medical District of Linyi People's Hospital, Linyi City, Shandong Province, China, from June 2013 to December 2016 were randomly divided into two groups. Patients in the observation group (aged 42 - 65 years) received dezocine-propofol combination as anesthesia, while those in the control group (aged 41 - 67 years) were anesthetized with fentanyl-propofol. Serum levels of pain and inflammatory mediators, as well as contents of immune response molecules were determined prior to, during and after colonoscopy using either enzyme-linked immunosorbent assay (ELISA) or electro-chemiluminescence kits.Results: There were no statistically significant differences in the serum levels of 5-hydroxytryptophan (5-HTP), 5-hydroxy indole acetic acid (5-HIAA), substance P (SP), prostaglandin E2 (PGE2), C-reactive protein (CRP), heat shock protein 70 (HSP70), Interleukin-1 β(IL-1β), adrenocorticotropic hormone (ACTH), Cortisol (Cor), Inositol (Ins), c-peptide (C-P), immunoglobulin G (IgG) and immunoglobulin A (IgA), complement 3 (C3) and complement 4 (C4) before and during colonoscopy between the two groups of patients. However, after the examination, serum levels of 5-HTP, 5-HIAA, SP, PGE2, CRP, HSP70, IL-1 beta, ACTH, Cor, Ins and C-P in the observation group were significantly lower than those in control group (p < 0.05), while IgG, IgA, C3 and C4 contents were significantly higher than those of the control group (p < 0.05).Conclusion: These results suggest that the analgesic effect of dezocine-propofol combination after colonoscopy examination is superior to that of fentanyl-propofol combination, due to its effectiveness in inhibiting inflammatory reactions and improving immune response.Keywords: Colonoscopy, Dezocine, Propofol Fentanyl, Pain mediators, Analgesic, Inflammatory reaction, Immune respons

Quantification of the influence of drugs on zebrafish larvae swimming kinematics and energetics

The use of zebrafish larvae has aroused wide interest in the medical field for its potential role in the development of new therapies. The larvae grow extremely quickly and the embryos are nearly transparent which allows easy examination of its internal structures using fluorescent imaging techniques. Medical treatment of zebrafish larvae can directly influence its swimming behaviours. These behaviour changes are related to functional changes of central nervous system and transformations of the zebrafish body such as muscle mechanical power and force variation, which cannot be measured directly by pure experiment observation. To quantify the influence of drugs on zebrafish larvae swimming behaviours and energetics, we have developed a novel methodology to exploit intravital changes based on observed zebrafish locomotion. Specifically, by using an in-house MATLAB code to process the recorded live zebrafish swimming video, the kinematic locomotion equation of a 3D zebrafish larvae was obtained, and a customised Computational Fluid Dynamics tool was used to solve the fluid flow around the fish model which was geometrically the same as experimentally tested zebrafish. The developed methodology was firstly verified against experiment, and further applied to quantify the fish internal body force, torque and power consumption associated with a group of normal zebrafish larvae vs. those immersed in acetic acid and two neuroactive drugs. As indicated by our results, zebrafish larvae immersed in 0.01% acetic acid display approximately 30% higher hydrodynamic power and 10% higher cost of transport than control group. In addition, 500 μM diphenylhydantoin significantly decreases the locomotion activity for approximately 50% lower hydrodynamic power, whereas 100 mg/L yohimbine has not caused any significant influences on 5 dpf zebrafish larvae locomotion. The approach has potential to evaluate the influence of drugs on the aquatic animal’s behaviour changes and thus support the development of new analgesic and neuroactive drugs

Evaluation of post hysterectomy vaginal cuff related complications and their management after different modes of hysterectomy

Background: Aim: To update the incidence of vaginal cuff related complications after different modes of hysterectomy and their management.Methods: The study was conducted in Jingzhou central hospital, Jingzhou, Hubei, China. Patient’s case files were reviewed who had undergone Hysterectomy from 1st Jan. 2013 - 31st Dec. 2014. The incidence of vaginal cuff related complications were retrospectively evaluated by different approaches. Data were collected according to our inclusion criteria and statistically analyzed its significance (P <0.05).Results: 887 patients underwent hysterectomy during 2 years of study period. Mean age was 54 ± 4 years. Overall incidence of vaginal cuff related complications were 34 (3.83%) which included vaginal cuff bleeding 12 (1.35%), vaginal cuff infections 16 (1.80%) and vaginal cuff dehiscence 6 (0.67%) without evisceration. Laparoscopic hysterectomy had higher incidence (6.12%), than open abdominal (2.56%) and vaginal (3.22%) hysterectomy. Incidences were significant (P = 0.032) to approaches of hysterectomy. The Incidence of vaginal cuff dehiscence between Laparoscopic and Open abdominal hysterectomy were significant (P = 0.015) but the incidence of vaginal cuff bleeding (P = 0.90) and vaginal cuff infection (P = 0.74) were not significant. Over all incidences were higher in malignancy (61%) than benign (20%).Conclusions: Study suggests that vaginal cuff bleeding, cuff infection, cuff dehiscence and evisceration are rare but not negligible which may lead into catastrophic conditions. Early diagnosis and appropriate management reduces further complications. Partial cuff dehiscence can be managed conservatively without surgical repair with satisfactory outcome

Machine Learning-Based Identification of Contaminated Images in Light Curves Data Preprocessing

Attitude is one of the crucial parameters for space objects and plays a vital role in collision prediction and debris removal. Analyzing light curves to determine attitude is the most commonly used method. In photometric observations, outliers may exist in the obtained light curves due to various reasons. Therefore, preprocessing is required to remove these outliers to obtain high quality light curves. Through statistical analysis, the reasons leading to outliers can be categorized into two main types: first, the brightness of the object significantly increases due to the passage of a star nearby, referred to as "stellar contamination," and second, the brightness markedly decreases due to cloudy cover, referred to as "cloudy contamination." Traditional approach of manually inspecting images for contamination is time-consuming and labor-intensive. However, We propose the utilization of machine learning methods as a substitute. Convolutional Neural Networks (CNN) and Support Vector Machines (SVM) are employed to identify cases of stellar contamination and cloudy contamination, achieving F1 scores of 1.00 and 0.98 on test set, respectively. We also explored other machine learning methods such as Residual Network-18 (ResNet-18) and Light Gradient Boosting Machine (lightGBM), then conducted comparative analyses of the results.Comment: 12 pages, 15 figure