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Acoustic emission (AE) as a non-destructive monitoring method is used to identify small damage in various materials effectively. However, AE signals acquired during the monitoring of oil and gas steel pipelines are always contaminated with noise. A noisy signal can be a threat to the reliability and accuracy of the findings. To address these shortcomings, this study offers a technique based on discrete wavelet transform to eliminate noise in these signals. The denoising performance is affected by several factors, including wavelet basis function, decomposition level, thresholding method, and the threshold selection criteria. Traditional threshold selection rules rely on statistical and empirical variables, which influence their performance in noise reduction under various conditions. To obtain the global best solution, a threshold selection approach is proposed by integrating particle swarm optimization and the late acceptance hill-climbing heuristic algorithms. By comparing five common approaches, the superiority of the suggested technique was validated by simulation results. The enhanced thresholding solution based on particle swarm optimization algorithm outperformed others in terms of signal-to-noise ratio and root-mean-square error of denoised AE signals, implying that it is more effective for the detection of AE sources in oil and gas steel pipelines.

he acoustic emission technique has been applied successfully for the identification, characterization, and localization of deformations in civil engineering structures. Numerous localization techniques, such as Modal Acoustic Emission, Neural Networks, Beamforming, and Triangulation methods with or without prior knowledge of wave velocity, have been presented. Several authors have conducted in-depth research in the localization of AE sources. However, existing review papers do not focus on the performance evaluation of existing source localization techniques. This paper discusses these techniques based on the number of sensors used and the geometry of the structures of interest. Furthermore, it evaluates them on the basis of their performance. At the end of this paper, a comparative analysis of existing methods has been presented based on their basic principles, key strengths, and limitations. A deep learning circular sensor cluster-based solution has the potential to provide a low-cost reliable localization solution for acoustic emission sources.

Cloud computing is a paradigm that has already evolved. Cloud computing moved widely to microservices from monoliths. The modular cloud application has gained attention for Microservices. Intensive network communication is required to call the interdependent microservices operating inside the cloud nodes. This research focuses on container-based microservices pre-distribution techniques and proposes two distribution strategies i.e. design pattern distribution and random distribution. The microservices are arbitrarily distributed to the available data centers in the random allocation method. While the microservices are clustered in the pattern distribution based on behavioral design patterns, which identify common contact patterns between entities. A custom-built modeling environment has been used to evaluate the proposed method. The findings revealed that the pre-distribution of microservices in accordance with the application architecture trend led to substantial less response time for the calls made to services hosted at geographically dispersed data centers.

Structural degradation takes place in pipelines with the passage of time. Hence. The restoration of proper functioning of these pipelines requires these defects to be identified and localized. Acoustic emission (AE) is a powerful non-destructive evaluation (NDE) technique for the detection of defects. Acoustic emission signals contain a significant amount of noise. In this paper, machine learning technique has been used to accurately classify and localize the corrosion defect. Experiments were performed on a 10’’ steel pipeline to show the relationship between the location of the corrosion defect and the acoustic emission signal. The results show that by using SVR, corrosion defect can identified and localized. This method is capable of providing a reference value for the real-time pipeline monitoring being operational in status, with broad application prospects.

Cloud computing is a rapidly growing paradigm which has evolved from having a monolithic to microservices architecture. The importance of cloud data centers has expanded dramatically in the previous decade, and they are now regarded as the backbone of the modern economy. Cloud-based microservices architecture is incorporated by firms such as Netflix, Twitter, eBay, Amazon, Hailo, Groupon, and Zalando. Such cloud computing arrangements deal with the parallel deployment of data-intensive workloads in real time. Moreover, commonly utilized cloud services such as the web and email require continuous operation without interruption. For that purpose, cloud service providers must optimize resource management, efficient energy usage, and carbon footprint reduction. This study presents a conceptual framework to manage the high amount of microservice execution while reducing response time, energy consumption, and execution costs. The proposed framework suggests four key agent services: (1) intelligent partitioning: responsible for microservice classification; (2) dynamic allocation: used for pre-execution distribution of microservices among containers and then makes decisions for dynamic allocation of microservices at runtime; (3) resource optimization: in charge of shifting workloads and ensuring optimal resource use; (4) mutation actions: these are based on procedures that will mutate the microservices based on cloud data center workloads. The suggested framework was partially evaluated using a custom-built simulation environment, which demonstrated its efficiency and potential for implementation in a cloud computing context. The findings show that the engrossment of suggested services can lead to a reduced number of network calls, lower energy consumption, and relatively reduced carbon dioxide emissions.

To determine the qualities of a good medical teacher from a trainee's perspective, to evaluate the best teaching method, and to explore the association of specialty and level of training with teaching methods and qualities of a medical teacher.The questionnaire-based cross-sectional survey was conducted in two tertiary care teaching hospitals in Lahore, Pakistan, from July 2019 to December 2020, and comprised all house officers and postgraduate residents. Data was collected using a self-administered questionnaire that had three sections: demographics, best method of teaching, and the characteristics of a good medical teacher. Data was analysed using SPSS 20.Of the 135 subjects, 56(41.5%) were males; 79(58.5%) were females; 76(56%) were junior trainees; and 77(57%) belonged to surgical specialties. The overall mean age was 27.6±2.4 years. Best teaching method identified by the trainees was 'asking of problem-based questions' 46(33.6%). Good communication skills 61(44.5%), and calm and non-humiliating demeanour 61(44.5%) were the most frequently identified qualities. More surgical trainees considered the generation of competition among learners as the best teaching method than the trainees from other specialties (p=0.001). House officers reported 'unbiased' (p=0.001) and 'moral and ethical' (p=0.001) significantly more frequently as a good trait in their teachers compared to the residents.The most important qualities in a medial teacher, as identified by the learners, were good communication skills and calm and polite attitude.

Background and objectives Esophageal cancer incidence is gradually increasing worldwide. Studies have looked at the pathological stage rather than clinical stage as predictor of survival. We looked at patients with complete pathological response to compare their survival outcomes to those who had residual disease after neoadjuvant treatment. Materials and methods All patients with esophageal cancer who underwent neoadjuvant treatment followed by resection at our institute were retrospectively reviewed. Overall survival and disease free survival were calculated for patients with complete pathological response and compared to those with residual disease using log rank test. Results Mean age of our patients was 51.08 years with standard deviation of 10.17 years. 39% belong to stage IIa while 5% belong to Stage IIb. 56% were Stage III. Final histopathological stage was recorded and both disease free and overall survival were calculated. 45% of our patients had complete pathological response. Patients with complete pathological response had mean survival of 62.73 months ± 17.02 compared to 41.42 months for patients who had residual disease. 5 year disease free survival was 58%. Conclusion Complete Pathological response significantly improves overall and disease free survival. It is also the predictor of long term survival.

Pleomorphic adenoma of submandibular gland is a very rare condition compared to that of parotid. We are here discussing a case of the same in a 40yrs old male with clinical, operative, and histological findings .

INTRODUCTION: Un descended testis carry a higher potential for malignant transformation than normally descended testis. Seminoma is the most frequent testicular tumor of the testicle in fourth decade of life and constitutes 60-65% of germ cell neoplasia, several histopathological characteristics have been evaluated and three type of pure seminoma have been described, classic, anaplastic and spermatocytic.

With the introduction of neoadjuvant chemoradiotherapy in patients with esophageal carcinoma, nutritional access has become essential to counter deleterious effects of dysphagia. Current NCCN guidelines do not recommend PEG prior to esophagectomy in these patients, but there is little evidence for this recommendation. The objective of this study was to compare outcomes in patients who underwent esophagectomy with or without prior PEG placement. We retrospectively reviewed 96 patients who underwent esophagectomy between 2005 and 2012 for esophageal carcinoma. Patients were divided into two groups; Group I (PEG +ve) and Group II (PEG −ve). Patient characteristics, operative variables, and post-operative complications were compared. χ 2 and Fisher’s test were used for categorical, while t test was used for interval variables. Median age was 51(18–70) years. Lower thoracic tumors were more common in Group I (69 vs. 63 %) (P = 0.04) and more patients underwent minimally invasive surgery in this group (50 vs. 2.6 %) (P

Background. Two common procedures for esophageal resection are Ivor Lewis esophagectomy and transhiatal esophagectomy. Both procedures have high morbidity rates of 20–46%. Minimally invasive esophagectomy has been introduced to decrease morbidity. We report initial experience of MIE to determine the morbidity and mortality associated with this procedure during learning phase.Material and Methods. Patients undergoing MIE at our institute from January 2011 to May 2013 were reviewed. Record was kept for any morbidity and mortality. Descriptive statistics were presented as frequencies and continuous variables were presented as median. Survival analysis was performed using Kaplan Meier curves.Results. We performed 51 minimally invasive esophagectomies. Perioperative morbidity was in 16 (31.37%) patients. There were 3 (5.88%) anastomotic leaks. We encountered 1 respiratory complication. Reexploration was required in 3 (5.88%) patients. Median operative time was 375 minutes. Median hospital stay was 10 days. The most frequent long-term morbidity was anastomotic narrowing observed in 5 (9.88%) patients. There were no perioperative mortalities. Our mean overall survival was 37.66 months (95% confidence interval 33.75 to 41.56 months). Mean disease-free survival was 24.43 months (95% CI 21.26 to 27.60 months).Conclusion. Minimally invasive esophagectomy, when performed in the learning phase, has acceptable morbidity and mortality.

To provide frequency and distribution pattern of various types of irregular red cell alloantibodies in patients with thalassemia major.This is a descriptive study conducted at two centers from January to December 2001. Purposive sampling was done and all patients diagnosed to have thalassemia major were included in the study. Antibody identification was carried out on serum employing commercial two-cell panel using standardized blood bank methods. If patients were found to have an irregular red cell alloantibody then the antibody identification was performed using 16 panel cells.A total of ninety-seven patients were included in the study. Fifty-three patients were males and 44 females. Mean age was 10.6 years. Irregular red cell alloantibodies were found in 9 (9.2%). Mean age of patients who developed red cell alloantibody was 11.9 years. Three (33.3%) patients developed anti-K while two (22.2%) had non-specific antibody. One patient each developed anti-D (11.1%) and anti-E (11.1%). Two had anti-D (11.1%) and anti-C while the other one (11.1%) developed anti-E and anti-K.We concluded that there is relatively high rate of alloimmunization in our set of patients when compared to data from our region. We also suggest that red cell alloimmunization should not be overlooked in patients receiving regular blood transfusions.

The objectives of this study were to assess the proportion of hepatitis C virus (HCV) reactors and to identify risk factors associated with HCV infection in volunteer blood donors in Karachi, Pakistan. Between 1 January 1998 and 31 December 2002, consecutive blood donations tested at two blood banks were used to assess the proportion of HCV sero-reactors donors. To evaluate the potential risk factors, a case-control study design was implemented to select cases and controls between 15 October 2001 and 15 March 2002. The overall seroprevalence of HCV in these blood donors was 1.8% (6349/35 1309). Trend analysis revealed a significant (P < 0.001) linear increase in proportions of HCV-seropositive donors from 1998 to 2002. Final multivariate logistic regression model showed that the cases were more likely than controls to have reported past hospitalization or to have received multiple injections. When a glass syringe was used to give therapeutic injections, it increased the adjusted odds of being HCV seropositive significantly more among cases than in controls and this relationship was stronger when injection was given by general medical practitioner than if the injection was given in hospital setting. Cases were more likely than controls to have reported sexual contact with multiple sexual partners. Primary prevention programmes focused on identified risk factors might help to curtail the spread of HCV infection in this community and in other similar settings in developing countries.