Comparative study between injection parecoxib and butorphanol for postoperative analgesia in laparotomy patients

Background: Pain is a complex, subjective experience comprising both physical and emotional components. Upper abdominal surgeries cause most intense pain and distress. Opioids and Nonsteroidal anti-inflammatory drugs are used for postoperative analgesia. Aim of this study was to compare the efficacy of analgesia between injection parecoxib and butorphanol.Methods: Prospective randomised comparative study included total 60 patients posted for laparotomy under general anaesthesia. Patients were randomly allocated in two groups. One group received injection paecoxib sodium (Group-P) and other group received injection Butorphanol (Group- B) half an hour before extubation. Pain score was recorded as per visual analogue scale at 0, 4,8,12 hours. The side effects if any were recorded and vomiting and sedation score was recorded.Results: Immediately in postoperative period VAS was less in Group B, but at 8 hours. VAS was less in Group P.Conclusions: Parecoxib has better quality of pain relief, minimal side effects compared to butorphanol which has good analgesia in immediate postoperative period

Applicability of T1-weighted MRI in the assessment of forensic age based on the epiphyseal closure of the humeral head

This work investigates the value of magnetic resonance imaging analysis of proximal epiphyseal fusion in research examining the growth and development of the humerus and its potential utility in establishing forensic age estimation. In this study, 428 proximal humeral epiphyses (patient age, 12-30years) were evaluated with T1-weighted turbo spin echo (T1 TSE) sequences in coronal oblique orientation on shoulder MRI images. A scoring system was created following a combination of the Schmeling and Kellinghaus methods. Spearman's rank correlation analysis revealed a significant positive relationship between age and ossification stage of the proximal humeral epiphysis (all subjects: rho=0.664, p<0.001; males: 0.631, p<0.001; females: rho=0.651, p<0.001). The intra- and inter-observer reliability assessed using Cohen's kappa statistic was =0.898 and =0.828, respectively. The earliest age of epiphysis closure was 17years for females and 18years for males. MRI of the proximal humeral epiphysis can be considered advantageous for forensic age estimation of living individuals in a variety of situations, ranging from monitoring public health to estimating the age of illegal immigrants/asylum seekers, minors engaged in criminal activities, and illegal participants in competitive sports, without the danger of radiation exposure

Optimized ANN-GA and experimental analysis of the performance and combustion characteristics of HCCI engine

HCCI (Homogeneous Charge Compression Ignition) engine has the benefit of operating at high thermal efficiency and low emissions of NOx and soot. However, it has challenges of complex combustion phase controlling and low operating range. This research work investigated the performance and combustion characteristics of HCCI engine with numerical simulations on ANSYS FLUENT and neural network models. The numerical and neural network results were validated by experimental observations with different fuel properties and reduced valve lifts for trapping of the exhaust gases. Experiments were performed on a SMART engine for different speeds and inlet air temperature, with various reference fuels (PRF30, PRF50, PRF70) and methanol to validate the CFD and ANN-GA observations. The engine performance was analyzed for IMEP, ISFC and thermal efficiency, which were found to be 8.2 bar, 205 g/kWh and 44.5% respectively as the optimum performance with PRF-70 fuel. The trapping of the residual gases was performed with various fuel blends in order to overcome the cyclic variations and to improve the operating zones near the knock boundary. The heat release rate was significantly reduced with trapped exhaust gases, and operating region was improved with the use of methanol fuel. Overall the trapping of the hot residual gases resulted in the maximum increase in the operating region by 12% and reduced cyclic variations by 15% for methanol fuel. The exhaust emissions were analyzed and ultra-low emissions of NOx at lean operating conditions were observed with the reduced valve lifts. The study results indicated thermal NO emissions on an average were decreased by 7.8%, CO emissions reduced by 6% and HC emissions increased by 9%. Methanol had ultra-low emissions of HC and CO, but higher emissions of NO and PRF30 had lower emissions of NO. However, ANN-GA model gave satisfactory combustion characteristics and emissions with respect to experimental results. Thus, CFD simulations, Neural Network methods and experimental study gave valuable thoughts of trapped residual gases approach on performance, combustion and emission characteristics of HCCI with PRF's and methanol fuel

Validation of Freehand Cervical Pedicle Screw Placement in Subaxial Spine Using the “Burcev Technique”: A Cadaveric Study

The present study attempted to validate the “Burcev freehand method” based on anatomical observations in Indian cadavers. The study was conducted on 32 cervical pedicle screws (CPSs) that were placed in four cadavers by the authors according to the “freehand technique,” described by Burcev et al, without the aid of fluoroscopy and the trajectory verified by computed tomography scans. The screws were designated as satisfactory, permissible, or unacceptable. Descriptive variables were represented in number and percentages, continuous variables were represented as mean ± standard deviation (SD). Of the 32 CPSs placed, 24 (75%) exhibited a satisfactory position, 1 (3%) exhibited a permissible position, and 7 (22%) exhibited an unacceptable position. Of the seven CPSs in the unacceptable group, four exhibited a lateral breach and three exhibited a medial breach, whereas the CPS in the permissible group exhibited a medial breach. The overall angle with contralateral lamina in the horizontal plane in terms of mean ± SD was 175.43 ± 2.82, 169.49, and 169.65 ± 6.46 degrees in the satisfactory, permissible, and unacceptable groups, respectively. In the sagittal plane, the screws exhibited an angle of 88.15 ± 3.56 degrees. No breach was observed superiorly or inferiorly. The “Burcev technique” is replicable with similar results in cadavers. Further studies must be conducted in a clinical setting to ensure its safety

Optimized ANN-GA and experimental analysis of the performance and combustion characteristics of HCCI engine

\u3cp\u3eHCCI (Homogeneous Charge Compression Ignition) engine has the benefit of operating at high thermal efficiency and low emissions of NOx and soot. However, it has challenges of complex combustion phase controlling and low operating range. This research work investigated the performance and combustion characteristics of HCCI engine with numerical simulations on ANSYS FLUENT and neural network models. The numerical and neural network results were validated by experimental observations with different fuel properties and reduced valve lifts for trapping of the exhaust gases. Experiments were performed on a SMART engine for different speeds and inlet air temperature, with various reference fuels (PRF30, PRF50, PRF70) and methanol to validate the CFD and ANN-GA observations. The engine performance was analyzed for IMEP, ISFC and thermal efficiency, which were found to be 8.2 bar, 205 g/kWh and 44.5% respectively as the optimum performance with PRF-70 fuel. The trapping of the residual gases was performed with various fuel blends in order to overcome the cyclic variations and to improve the operating zones near the knock boundary. The heat release rate was significantly reduced with trapped exhaust gases, and operating region was improved with the use of methanol fuel. Overall the trapping of the hot residual gases resulted in the maximum increase in the operating region by 12% and reduced cyclic variations by 15% for methanol fuel. The exhaust emissions were analyzed and ultra-low emissions of NO\u3csub\u3ex\u3c/sub\u3e at lean operating conditions were observed with the reduced valve lifts. The study results indicated thermal NO emissions on an average were decreased by 7.8%, CO emissions reduced by 6% and HC emissions increased by 9%. Methanol had ultra-low emissions of HC and CO, but higher emissions of NO and PRF30 had lower emissions of NO. However, ANN-GA model gave satisfactory combustion characteristics and emissions with respect to experimental results. Thus, CFD simulations, Neural Network methods and experimental study gave valuable thoughts of trapped residual gases approach on performance, combustion and emission characteristics of HCCI with PRF's and methanol fuel.\u3c/p\u3

Real TIME License Plate Number Extraction of Non-helmet Person Using YOLO Algorithm

One of the problems in traffic regulations in India is riding motorcycle/mopeds without helmet, which increases accident sand deaths. In the existing system, the traffic police monitor the traffic violations through CCTV recordings, and in case if the rider without helmet is detected, then its vehicle number is recorded. But the constant monitoring is required to control the traffic rule violation which happens very frequently. To overcome these problems, we will require a system which would automatically handle traffic violations for non-helmet rider and thus would automatically extract the vehicles' license plate number. The various research has successfully done in this area using CNN, R-CNN, LBP, HoG, HaaR features etc., but the results are limited with respect to efficiency, accuracy and speed. To overcome the problems associated with it, we develop a Non-Helmet Rider detection system, which attempts to satisfy the automation of detecting the traffic violation of non-helmet person and extracting the vehicles' license plate number. The main principle involved in this system is Object Detection using Deep Learning at three levels. The person, motorcycle/moped is detected at first level using YOLOv2, helmet at second level using YOLOv3, License plate at the last levelusing YOLOv2