Relationship Between Self-efficacy and Chinese Language Speaking Anxiety of International Students at Northeast Normal University

The existing research was conducted in order to explore the correlation between Self-efficacy and Chinese Language Speaking Anxiety among International students at NENU, Changchun, China.  In that respect the intention of this survey is to probe whether international students’ Chinese Language Speaking Anxiety reveal significant variation with respect to gender, Nationality, Time lived in China, Number of Chinese Courses learned and Frequency of communication with Chinese friends in Chinese language. The research group involved 131 international students i.e.  (70 males =53% and 61 females= 47%) from NENU. The study employed the quantitative method conducted through surveys by adapted questionnaires developed by Horowitz’s (1986) and Graumer Erickson, A.S.,Soukup, J.H.,Noonan, P.M., &McGurn, L.(2016). The data were examined by means of independent T-test, one-way ANOVA and Pearson’s correlation approaches. T-test reveals high degree of Chinese Language Speaking Anxiety among international students but found no any considerable distinction in terms of gender. While ANOVA results show a only significance difference between the numbers of Chinese courses the participants learnt. In last A Pearson’s r data revealed a weak positive association between Self-efficacy and Chinese Language Speaking Anxiety among International students at NENU. Keywords: Self-efficacy, Chinese Language Speaking Anxiety DOI: 10.7176/JEP/10-2-0

IMPACTS OF TRANSFUSION BLOOD ON FUNCTIONS OF KIDNEYS AFTER ORTHOPEDIC SURGERY

Objective: The impact of the transfusion of blood before the surgery on the function of the kidneys remained as a part of subject in different research works. The aim of this study is to investigate the impacts of transfusion of blood on the function of kidneys after surgery in the patients who underwent orthopedic surgical intervention. Methodology: Total one hundred and thirty-six patients who underwent surgical intervention because of different orthopedic pathologies from July 2018 to January 2019 were under evaluation. The division of the patients carried out into 2 groups depending upon the amount of the transfusion of blood. Total 69.80% (n: 95) patients who found with transfusion of lower than 3 units were the part of Group-1 & 30.20% (n: 41) patients who received three or greater than 3 blood units were the part of Group-2. Results: We found no statistical disparities between the patients of both groups before surgery regarding sex, hypertension, DM, failure of the kidney & habits of cigarette smoking. No disparities between the patients of both group regarding stay in hospital after surgery, pulmonary and associated other complications & mortality. When the comparison of the blood parameters of the patients of both groups carried out describing the functions of kidneys and other organ systems, we detected no significant disparity. Conclusion: Transfusions of blood have no negative impacts on after surgery BUN & levels of creatinine in the patients with underwent surgery for the orthopedic complications. KEY WORDS: Transfusion, Arthroplasty, Blood, Kidney, Orthopedic, Surgery, Pulmonary, Intervention

Frequency of Stress among Medical Students

Stress arises once an individual is unable to handle a situation. Continuous stress may lead to certain complications. Objective: To see the frequency of stress among medical students. Material and Methods: This cross-sectional study included 182 medical students of the fourth year and final year from different medical colleges of Pakistan. A pre-designed questionnaire was served to the students. Different questions about stress, its reasons, and handling techniques were asked. Data were analyzed with SPPS V.23. Results: 135 (88.2%) out of 182 medical students including 69 females (45.09%) and 66 males (43.13%) reported that they faced different kinds of stress i.e. continuous or random stress during their academic and clinical rotations.  Different kinds of handling techniques were isolation, handing out with friends, focusing on studies, etc. Conclusion: Most of the medical students face stress during their academics and clinical rotations. This stress may be for a smaller time or longer time depending on the nature of stress and ability of the student to cope with the stress

A Framework for Burnt Area Mapping and Evacuation Problem Using Aerial Imagery Analysis

The study aims to develop a holistic framework for maximum area coverage of a disaster region during a bushfire event. The monitoring and detection of bushfires are essential to assess the extent of damage, its direction of spread, and action to be taken for its containment. Bushfires limit human’s access to gather data to understand the ground situation. Therefore, the application of Unmanned Aerial Vehicles (UAVs) could be a suitable and technically advanced approach to grasp the dynamics of fires and take measures to mitigate them. The study proposes an optimization model for a maximal area coverage of the fire-affected region. The advanced Artificial Bee Colony (ABC) algorithm will be applied to the swarm of drones to capture images and gather data vital for enhancing disaster response. The captured images will facilitate the development of burnt area maps, locating access points to the region, estimating damages, and preventing the further spread of fire. The proposed algorithm showed optimum responses for exploration, exploitation, and estimation of the maximum height of the drones for the coverage of wildfires and it outperformed the benchmarking algorithm. The results showed that area coverage of the affected region was directly proportional to drone height. At a maximum drone height of 121 m, the area coverage was improved by 30%. These results further led to a proposed framework for bushfire relief and rescue missions. The framework is grounded on the ABC algorithm and requires the coordination of the State Emergency Services (SES) for quick and efficient disaster response

Strategies to improve coverage of typhoid conjugate vaccine (TCV) immunization campaign in Karachi, Pakistan

The emergence and spread of extensively drug-resistant (XDR) typhoid in Karachi, Pakistan led to an outbreak response in Lyari Town, Karachi utilizing a mass immunization campaign with typhoid conjugate vaccine (TCV), Typbar TCV®. The mass immunization campaign, targeted Lyari Town, Karachi, one of the worst affected towns during the XDR typhoid outbreak. Here we describe the strategies used to improve acceptance and coverage of Typbar TCV in Lyari Town, Karachi. The mass immunization campaign with Typbar TCV was started as a school- and hospital-based vaccination campaign targeting children between the age of 6 months to 15 years old. A dose of 0.5 mL Typbar TCV was administered intramuscularly. A mobile vaccination campaign was added to cope with high absenteeism and non-response from parents in schools and to cover children out of school. Different strategies were found to be effective in increasing the vaccination coverage and in tackling vaccine hesitancy. Community engagement was the most successful strategy to overcome refusals and helped to gain trust in the newly introduced vaccine. Community announcements and playing typhoid jingles helped to increase awareness regarding the ongoing typhoid outbreak. Mop-up activity in schools was helpful in increasing coverage. Networking with locally active groups, clubs and community workers were found to be the key factors in decreasing refusals

Civil infrastructure damage and corrosion detection: an application of machine learning

Automatic detection of corrosion and associated damages to civil infrastructures such as bridges, buildings, and roads, from aerial images captured by an Unmanned Aerial Vehicle (UAV), helps one to overcome the challenges and shortcomings (objectivity and reliability) associated with the manual inspection methods. Deep learning methods have been widely reported in the literature for civil infrastructure corrosion detection. Among them, convolutional neural networks (CNNs) display promising applicability for the automatic detection of image features less affected by image noises. Therefore, in the current study, we propose a modified version of deep hierarchical CNN architecture, based on 16 convolution layers and cycle generative adversarial network (CycleGAN), to predict pixel-wise segmentation in an end-to-end manner using the images of Bolte Bridge and sky rail areas in Victoria (Melbourne). The convolutedly designed model network proposed in the study is based on learning and aggregation of multi-scale and multilevel features while moving from the low convolutional layers to the high-level layers, thus reducing the consistency loss in images due to the inclusion of CycleGAN. The standard approaches only use the last convolutional layer, but our proposed architecture differs from these approaches and uses multiple layers. Moreover, we have used guided filtering and Conditional Random Fields (CRFs) methods to refine the prediction results. Additionally, the effectiveness of the proposed architecture was assessed using benchmarking data of 600 images of civil infrastructure. Overall, the results show that the deep hierarchical CNN architecture based on 16 convolution layers produced advanced performances when evaluated for different methods, including the baseline, PSPNet, DeepLab, and SegNet. Overall, the extended method displayed the Global Accuracy (GA); Class Average Accuracy (CAC); mean Intersection Of the Union (IOU); Precision (P); Recall (R); and F-score values of 0.989, 0.931, 0.878, 0.849, 0.818 and 0.833, respectively

Drone-as-a-Service (DaaS) for COVID-19 self-testing kits delivery in smart healthcare setups: A technological perspective

Drones have gained increasing attention in the healthcare industry for mobility and accessibility to remote areas. This perspective-based study proposes a drone-based sample collection system whereby COVID-19 self-testing kits are delivered to and collected from potential patients. This is achieved using the drone as a service (DaaS). A mobile application is also proposed to depict drone navigation and destination location to help ease the process. Through this app, the patient could contact the hospital and give details about their medical condition and the type of emergency. A hypothetical case study for Geelong, Australia, was carried out, and the drone path was optimized using the Artificial Bee Colony (ABC) algorithm. The proposed method aims to reduce person-to-person contact, aid the patient at their home, and deliver any medicine, including first aid kits, to support the patients until further assistance is provided. Artificial intelligence and machine learning-based algorithms coupled with drones will provide state-of-the-art healthcare systems technology

Comparison of Mckenzie approach versus Lumbar Stabilization Exercises in the treatment of chronic low back pain

Introduction: Lumbar stabilization and McKenzie exercises are becoming a popular trend for managing chronic low back pain though it is currently not known whether lumbar stabilization exercises produce better results in improving functional status compared to McKenzie approach. The purpose of this study was to determine the effectiveness of the McKenzie approach versus lumbar stabilization in the treatment of chronic low back pain. Material & Methods: This was a randomized controlled trial. Lottery method was used to randomly divide individuals who fulfilled inclusion criteria into 2 groups. Assessments of the patients were done in OPD. Baseline assessment was done on day 1 and post intervention assessment was done after 2 weeks. A total of 8 treatment sessions spread across 2 weeks were given (4 days per week). Data were assessed at baseline level and post intervention. Data was entered and analysed by SPSS version 21. Results: A total of 28 females and 02 males (mean age of 50.88 ±12.29) participated in the study. After 02 weeks of intervention, both treatment groups showed improvement in decreasing pain and improving functional status. The lumber stabilization group showed significant gains on Numeric Pain Rating Scale and (p=0.001) and Modified Oswestry Disability Index (p=0.001) compared to the Mckenzie group. Conclusion: Patients in both lumber stabilisation and McKenzie groups showed significant improvement, however, the patients in lumbar stabilization group were superior than the patients in McKenzie group on the selected outcomes