Intravenous Lidocaine Infusion with Single Low-Dose Ketamine as an Adjuvant to General Anesthesia in Posterior Spine Fusion

Background: Posterior spinal fusion (PSF) is a common surgical operation used to correct degeneration of the lumbar spine with considerable postoperative pain. The primary objective of this study is to compare the total intraoperative and postoperative opioid consumption and numeric pain scale during the first 24 hours after surgery between the lidocaine/ketamine group and the narcotic-only group. Materials and Methods: Sixty adult patients (age 18–65 years) scheduled for elective PSF were included. Patients were divided randomly into either the lidocaine/ketamine group (LK group), who received lidocaine and ketamine injection in addition to usual perioperative narcotic analgesia, and the narcotic-only group (N group) who depended on narcotics only. The primary outcome measures were total intraoperative and postoperative opioid consumption and pain scores during the first 24 hours postoperatively. The secondary outcome measures were sedation score, intravenous rescue analgesia, postoperative nausea and vomiting, and pruritis during the first 24 hours postoperatively. Results: Patients in the LK group had lower intraoperative fentanyl consumption (216.3 ± 28.8 μg) than those in the N group (363 ± 35 μg). The LK group consumed less morphine during the first 24 hours after surgery (49.5 ± 6.0 mg) than the N group did (57.8 ± 8.6 mg). The LK group had lower pain scores at all-time intervals during the first 24 hours (2, 6, 12, and 24 hours) than the N group did. Conclusions: Intraoperative lidocaine infusion with low-dose ketamine reduced opioid consumption and pain scores in patients undergoing PSF

Association of interleukin-6 level and DNA polymorphism in type 2 diabetic patients in Kirkuk city

The basic inflammatory factor interleukin-6 plays an important role in the inflammatory response. It has been shown that IL-6 has a role in insulin resistance and T2DM. The IL-6 gene is found on chromosome 7p15-p21 in humans, it works via a receptor composed of two components, the IL-6 receptor, and gp130. Single nucleotide polymorphisms in the regulatory areas of IL-6R genes influence their expression levels and are linked to a higher risk of T2DM. There were 80 T2DM patients and 80 healthy people enrolled in the present work. Fasting blood glucose levels, HbA1C, and IL-6 concentrations were estimated in both groups. The allelic frequencies of 2 single nucleotide polymorphisms (rs2229238, rs4845625) were identified by PCR-SSP. In this study, we found that the fasting blood sugar levels, HbA1c, and IL-6 levels were statistically highly significant in patients in comparison with controls. In regarding the association of genotypic (CC, CT, TT) and allelic frequencies of rs2229238, and rs4845625 polymorphism of the gene IL6R, and prevalence of diabetes mellitus. The results of PCR-SPP products of rs2229238 (C/T) of the IL6R gene indicated the significant correlation the rs4845625 IL6R polymorphism with T2DM, where no significant association was observed between these genotypes (CC, CT, TT) and allelic (T) frequencies of rs2229238 as a risk factor and T2D

Multilevel Thresholding for Image Segmentation Using an Improved Electromagnetism Optimization Algorithm

Image segmentation is considered one of the most important tasks in image processing, which has several applications in different areas such as; industry agriculture, medicine, etc. In this paper, we develop the electromagnetic optimization (EMO) algorithm based on levy function, EMO-levy, to enhance the EMO performance for determining the optimal multi-level thresholding of image segmentation. In general, EMO simulates the mechanism of attraction and repulsion between charges to develop the individuals of a population. EMO takes random samples from search space within the histogram of image, where, each sample represents each particle in EMO. The quality of each particle is assessed based on Otsu’s or Kapur objective function value. The solutions are updated using EMO operators until determine the optimal objective functions. Finally, this approach produces segmented images with optimal values for the threshold and a few number of iterations. The proposed technique is validated using different standard test images. Experimental results prove the effectiveness and superiority of the proposed algorithm for image segmentation compared with well-known optimization methods

Developing Artificial Neural Network and Multiple Linear Regression Models to Predict the Ultimate Load Carrying Capacity of Reactive Powder Concrete Columns

The study focuses on development a model to predict the ultimate load carrying capacity of Reactive Powder Concrete (RPC) columns. Two different statistical methods regression techniques (RT) and the artificial neural network (ANN) methods were used for determining the RPC columns ultimate load carrying capacity. The data is collected from three experimental studies the first used to develop the model and the other two used as a case study. Experimental results used as input data to develop prediction models. Two different techniques adopted to develop the models the first was Artificial Neural Network (ANN) and the second was multi linear regression techniques (RT). The models use to predict the ultimate load carrying capacity of RPC columns. To predict the ultimate load carrying capacity of RPC columns four input parameters were identified cross-section, micro steel fiber volume fraction content, compressive strength and main steel reinforcement area. Both models build with assistance of MATLAB software. The results exhibit that the cross section area has most significant effect on ultimate load carrying capacity. The performance of ANNs with different architecture was considered to adopt the pest ANN. An ANN with one layer consist of 7 neurons provide the best prediction. The results of this investigation indicate that ANNs have strong potential as statistical method for prediction the ultimate load carrying capacity of RPC columns. Keywords: Reactive powder concrete, artificial neural network, multiple linear regressions, ultimate load carrying capacity, Statistical analysis

Design of optimal rule-based controller for plug-in series hybrid electric vehicle

International audienceEnergy consumption of Hybrid Electric Vehicles (HEV) strongly depends on the adopted energy management strategy (EMS). Rule-Based (RB) controllers are the most commonly used for their ability of integration in real-time applications. Unlike global optimization routines, RB controllers do not ensure optimal energy savings. This study presents a methodology to design a close-to-optimal RB controller derived from global optimization strategies. First, dynamic programming (DP) optimization is used to derive the optimal behaviour of the powertrain components on the Worldwide Harmonized Light Vehicles Test Cycle (WLTC), and then, the resulting performance of the powertrain components is used to design an optimized RB energy management strategy. Furthermore, the strategy is developed to cope with the variations in trip length and traffic conditions. The plug-in series hybrid electric vehicle is modelled using the energetic macroscopic representation (EMR). Results show that the proposed optimal RB controller is only consuming 1-2% more fuel compared to DP controllers and is resulting in a 13-16% less fuel consumption compared to basic RB controllers

Molecular detection of Toxoplasma gondii specific repeat element in blood of recurrent aborted women by real-time PCR

Toxoplasmosis caused by ingestion of raw or undercooked meat contains tissue cyst or contaminated food or water with oocyst of Toxoplasma gondii. This parasite is prevalent in humans, domestic and wild animals and is causative agent of abortion and congenital abnormalities. Methods: From october-2019 to April 2020, blood and serum samples were collected from 63 women with recurrent abortion. Serum samples were used for identification of anti-Toxoplasma IgM and IgG antibodies by ELISA technique. Real time- Polymerase Chain reaction technique utilized for revealing of the DNA of Toxoplasma gondii in the blood specimens. Presented study results showed the high aborted women 33 (52%) in age group (20-29), and high number of aborted women 36 (57%) have 3-6 abortions. Serodiagnosis results of 63 aborted women showed that 19 (30%) were seropositive for only IgG antibody, 6(10%) were seropositive for IgM antibody, and 6 (10%) were positive for both IgG and IgM antibodies. Molecular diagnosis of T. gondii DNA infection by RT- PCR for amplification of repeat region 529 bp of T. gondii DNA, revealed that only 7 (11.1%) blood samples were positive. RT-PCR assay was more sensitive and specific than serologic ELISA method in diagnosis of Toxoplasma gondii infection in recurrent aborted women

Direct Precipitation and Characterization of ZnO Nanoparticles

ZnO nanoparticles are prepared through hydrolysis and condensation of zinc acetate dihydrate by potassium hydroxide in alcoholic medium at low temperatures. Thermal gravimetric analysis (TGA) of the precursor is made in order to specify the temperature range over which the weight loss and thermal effect are significant. X-ray diffraction of the as-prepared specimens shows that the hexagonal (a=3.2459 Å, c=5.1999 Å) structure is the predominant crystallographic structure. According to Scherer’s formula, the average size of the nanoparticles is 22.4 ± 0.6 nm. The structural properties of the synthesized ZnO nanoparticles have been confirmed using the TEM micrographs. The optical energy gap of the ZnO nanoparticles, as obtained from applying Tauc’s equation, is equal to 3.52 eV, which is higher than that of the bulk material. Absorption peak of the as-prepared sample is 298 nm which is highly blue shifted as compared to the bulk (360 nm). Large optical energy gap and highly blue shifted absorption edge confirm that the prepared ZnO nanoparticle exhibits strong quantum confinement effect

The Culture of Peace and the Prevention of Terrorism from the Perspectives of Islamic Education and the United Nations

Terrorism is an unfamiliar phenomenon to the Islamic religion and it is in opposition to its doctrine. It leads to the loss of innocent lives, destruction of properties, spreading rumors, terrorizing the innocents and destabilization. All this makes fighting and preventing the phenomenon of terrorism the duty of all human beings. This study aimed to highlight and clarify the concept of the culture of peace and the prevention of terrorism from the perspective of Islamic Education and the United Nations

The Influence of Services Marketing Mix (7 Ps.) and Subjective Norms on Customer’s Satisfaction in Islamic Banks of Palestine

The purpose of this study was to examine the relationship between services marketing mix (product, price, place, promotion, people, process and physical evidence) on customer Satisfaction. Additionally, this study also explored the role of subjective norms towards customer satisfaction in Islamic Banks of Palestine. Customer satisfaction is one of the essential factors for the success of a company. In order to achieve the high customer satisfaction, companies must know when and how their customers are satisfied about the products and services. The majority of companies follow a conventional marketing strategy, but some companies choose to follow a religious or spiritual marketing strategy such as the Islamic marketing strategy. Conventional marketing strategies satisfy the customers based on the current needs of the customer, whereas, Islamic marketing strategies satisfy the customers based on the human values, marketing cultures, and Islamic rules and regulations (shariah laws). Structural equation model was used for the testing of hypothesized relationships. Finally, study concluded that marketing mix and subjective norm significantly influence on customer satisfaction in Islamic Banking context. Keywords: Services marketing mix (7Ps), Subjective Norms, Customer Satisfactio